{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9852739","patent":{"patent_number":"US-9852739","title":"Method and arrangement for controlling smoothing of stationary background noise","assignee":null,"inventors":[],"filing_date":"2016-02-09T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L"],"num_claims":30,"abstract":"In a method for coding of information for enhancing a background noise representation, voice activity of an input speech signal is determined. A noisiness parameter is determined for an inactive speech signal, wherein the noisiness parameter is based on a ratio of prediction gains of two Linear Predictive Coder (LPC) prediction filters with different orders. The noisiness parameter is quantized, and the quantized noisiness parameter is encoded for transmission."},"analysis":{"summary":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** patent (US-9852739) introduces a sophisticated method for enhancing background noise representation during information coding, resulting in clearer speech and improved audio quality. The core innovation lies in its intelligent control over the smoothing of stationary background noise.\n\nThe primary problem this invention solves is the degradation of speech intelligibility and overall audio experience caused by pervasive background noise in communication systems. Traditional noise reduction techniques often fall short, either by failing to adequately suppress complex stationary noise or by introducing undesirable artifacts that distort speech.\n\nTechnically, this patent approaches the problem by first determining the voice activity of an input speech signal. For segments identified as 'inactive speech' (i.e., background noise), it calculates a unique 'noisiness parameter'. This parameter is ingeniously derived from the ratio of prediction gains of two Linear Predictive Coder (LPC) prediction filters, each operating with a different order. This dual-filter analysis provides a more granular and accurate assessment of the noise characteristics than conventional methods. The determined noisiness parameter is then quantized and encoded for efficient transmission, allowing receiving systems to adaptively apply optimal noise smoothing.\n\nThe business value and applications of this technology are substantial. It promises to significantly enhance user experience in telecommunications, virtual conferencing, and voice-controlled devices by delivering superior audio clarity. Companies can gain a competitive advantage by offering products and services with noticeably better sound quality, reducing user fatigue and improving communication efficiency. This patent also has strong implications for broadcasting, content creation, and even assistive listening devices.\n\nThe market opportunity is vast, spanning across consumer electronics, enterprise communication solutions, and specialized audio equipment. As the demand for high-fidelity audio in increasingly noisy environments grows, this patent provides a foundational technology for next-generation audio processing, enabling more natural and effective human-to-human and human-to-machine interactions.","layman_explanation":"### What Problem Does This Solve?\n\nImagine you're on an important conference call, but your colleague's dog is barking in the background, or there's the constant hum of an air conditioner. It's distracting, makes it hard to focus, and often leads to miscommunications. This isn't just annoying; it costs businesses time and money due to reduced productivity and increased effort to understand each other. Existing solutions often try to mute *all* background noise, which can make people's voices sound unnatural, robotic, or cut out words. They struggle to differentiate effectively between important speech and persistent, but non-speech, background sounds without compromising voice quality. The core problem is achieving truly clear, natural-sounding speech in noisy environments without introducing new audio artifacts.\n\n### How Does It Work?\n\nThis patent, titled **Method and Arrangement for Controlling Smoothing of Stationary Background Noise**, offers a sophisticated solution. Think of it like a highly intelligent sound engineer built into your device. First, it's always listening to determine if someone is speaking (this is called 'voice activity'). When it detects that no one is speaking – meaning it's just background noise – it doesn't just try to silence it. Instead, it gets smart about *what kind* of noise it is.\n\nIt uses a clever trick involving two 'listening tools' called Linear Predictive Coder (LPC) filters, but each tool listens with a different 'focus' or 'order'. One might listen for the broad characteristics of the background hum, while the other listens for finer details. By comparing what these two tools 'hear' about the noise, it calculates a unique 'noisiness parameter.' This parameter is essentially a sophisticated way of saying, 'This particular background noise is exactly *this* steady and has *these* specific characteristics.' This precise understanding allows it to adaptively and intelligently control how much to 'smooth out' or reduce that specific stationary background noise. This 'noisiness parameter' is then efficiently packaged and sent along with the audio, so the receiving end knows precisely how to clean up the sound without making the speaker's voice sound unnatural.\n\n### Why Does This Matter?\n\nThis technology matters because it promises a significant leap in audio quality across almost every communication medium. For businesses, this means:\n\n*   **Enhanced Productivity:** Clearer calls lead to fewer misunderstandings, faster decision-making, and less communication fatigue for remote teams and clients.\n*   **Improved Customer Experience:** Call centers can deliver superior service, reducing frustration for both agents and customers. Products like smart speakers or voice assistants will become more reliable and intuitive, boosting user satisfaction.\n*   **Competitive Advantage:** Companies that integrate this innovation can differentiate their products (e.g., phones, headsets, conferencing platforms) by offering superior audio quality, attracting and retaining users. Imagine a virtual meeting platform that consistently offers the best sound clarity, regardless of participants' environments.\n*   **Cost Savings:** By improving communication efficiency, businesses can reduce operational costs associated with prolonged calls or repeated explanations.\n\nThis patent moves beyond basic noise cancellation to intelligent noise *management*, ensuring that the business value of clear communication is fully realized. It's about making technology disappear into the background so that human connection can take center stage.\n\n### What's Next?\n\nThis innovation is poised to become a foundational component in next-generation audio processing. We can expect to see its principles integrated into new generations of smartphones, smart home devices, automotive communication systems, and professional broadcasting equipment. As AI and voice interfaces become more prevalent, the demand for truly robust and natural-sounding audio will only grow. This patent provides a pathway for significant advancements in these areas, potentially leading to more intuitive human-computer interaction and a richer, less fatiguing auditory experience in our increasingly connected and noisy world. Early adoption and strategic integration of this patent's methodologies could yield substantial competitive benefits and strong ROI for forward-thinking companies.","technical_analysis":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** patent (US-9852739) outlines a highly innovative approach to enhancing background noise representation within information coding, with a direct impact on speech signal processing. This detailed technical breakdown focuses on the system's architecture, algorithmic specifics, and potential implications for developers and engineers.\n\n**Technical Architecture and Signal Flow:**\n\nThe fundamental architecture proposed by this patent involves a sequential processing chain. An input speech signal first enters a Voice Activity Determination (VAD) module. This VAD module classifies incoming audio frames into either 'active speech' or 'inactive speech' (representing periods dominated by noise or silence). The critical divergence from conventional systems occurs in the processing of these 'inactive speech' segments.\n\nFor inactive speech signals, the system initiates the determination of a 'noisiness parameter'. This parameter is not a simple energy threshold but a sophisticated metric designed to characterize the stationary background noise. This parameter is then quantized to convert its continuous value into a discrete representation, which is subsequently encoded for transmission alongside or as part of the primary audio stream. The encoded noisiness parameter can then be utilized by a decoder or post-processing unit at the receiving end to precisely control the application of noise smoothing, thereby optimizing the background noise representation.\n\n**Algorithm Specifics: The Dual LPC Filter Approach:**\n\nThe core algorithmic innovation lies in the method for determining the noisiness parameter. It is based on the ratio of prediction gains of two Linear Predictive Coder (LPC) prediction filters, each with a different order.\n\n*   **Linear Predictive Coding (LPC):** LPC is a well-established technique in speech processing used to model the spectral envelope of a signal. An LPC filter, typically an all-pole filter, estimates the current sample as a linear combination of past samples. The 'prediction gain' is a measure of how much the prediction process reduces the power of the signal; a higher prediction gain indicates that the signal is more predictable (e.g., voiced speech), while a lower gain suggests a more random or noise-like signal.\n*   **Dual-Filter Strategy:** The patent's ingenuity is in using *two* LPC filters with *different orders* (e.g., an 8th-order filter and a 16th-order filter). A lower-order LPC filter captures the broader spectral characteristics, while a higher-order filter can model finer spectral details. For instance, stationary background noise often has a relatively flat or slowly varying spectrum. The prediction gains from filters of different orders will react differently to the underlying signal structure. If the signal is predominantly stationary noise, the prediction gains from both filters might be relatively low and similar. However, if there are subtle, non-stationary components or residual speech, the prediction gain ratio might deviate, providing a more robust indicator of 'noisiness' than a single filter's gain or other simpler metrics.\n*   **Ratio of Prediction Gains:** Taking the *ratio* of these two prediction gains normalizes the measurement and provides a highly discriminative feature. This ratio effectively quantifies how 'predictable' the signal is at different levels of spectral resolution. A signal that is highly predictable by a higher-order filter but less so by a lower-order one might indicate different characteristics than one where both filters struggle equally. This enables a more nuanced understanding of the background noise's structure and variability.\n\n**Quantization and Encoding:**\n\nThe noisiness parameter, being a continuous value, undergoes quantization. This process maps the continuous range of the parameter to a finite set of discrete values. This step is crucial for:\n\n1.  **Bit-rate Efficiency:** Quantized values require fewer bits for representation, making the subsequent encoding and transmission highly efficient.\n2.  **Robustness to Channel Errors:** Discrete values are less susceptible to corruption during transmission than continuous ones.\n3.  **Interoperability:** It allows for the parameter to be standardized and integrated into various audio codecs (e.g., G.729, AMR, Opus) as side information.\n\nThe encoded noisiness parameter is then transmitted. At the receiver, this encoded information can be used to dynamically adjust noise smoothing algorithms (e.g., spectral subtraction, Wiener filtering, or Kalman filtering) to match the perceived noisiness of the background. This adaptive control ensures that noise reduction is applied optimally, minimizing speech distortion while maximizing noise suppression.\n\n**Integration Patterns and Performance Characteristics:**\n\nThis technology can be integrated into existing audio processing pipelines at several points: pre-processing before encoding, within the encoder as side information, or as part of a post-processing enhancement module at the decoder. Its computational overhead for the dual-LPC analysis is relatively low compared to complex deep learning-based noise reduction methods, making it suitable for real-time, low-power applications (e.g., mobile devices, embedded systems).\n\nThe performance characteristics would include superior speech intelligibility in noisy environments, reduced musical noise or other artifacts common in aggressive noise reduction, and robust operation across a wide range of stationary background noise types. The adaptive nature, driven by the noisiness parameter, allows for a more 'natural' sounding output compared to fixed-parameter systems.\n\n**Code-Level Implications:**\n\nDevelopers implementing this patent would need to:\n\n*   Develop or integrate a robust VAD module.\n*   Implement two LPC analysis modules capable of calculating prediction gains for different orders.\n*   Design a function to compute the ratio of these prediction gains.\n*   Implement a quantization scheme for the resulting noisiness parameter.\n*   Integrate an encoding mechanism for this quantized parameter, potentially as a new field in an existing audio frame structure or as a separate side channel.\n*   At the decoder, implement a corresponding decoding module and a noise smoothing algorithm that can dynamically adjust its parameters based on the received noisiness parameter.\n\nThis patent provides a solid foundation for building highly effective, computationally efficient, and perceptually pleasing noise reduction systems. Its technical elegance lies in deriving a powerful discriminative feature from well-understood signal processing primitives, paving the way for superior audio experiences in diverse applications.","business_analysis":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** patent (US-9852739) represents a significant business opportunity within the rapidly expanding audio technology market. Its innovative approach to intelligently managing stationary background noise smoothing addresses a critical pain point across numerous industries, positioning it as a valuable asset for companies seeking a competitive edge.\n\n**Market Opportunity Size:**\n\nThe global market for audio processing and enhancement technologies is vast and continually growing, driven by the proliferation of voice-enabled devices, remote work, online content creation, and immersive entertainment. This includes:\n\n*   **Telecommunications:** The global VoIP market alone is projected to reach over $194 billion by 2024. Clear audio is non-negotiable for business communications, call centers, and consumer services.\n*   **Consumer Electronics:** Smart speakers, headphones, smartphones, and automotive infotainment systems are increasingly reliant on robust voice interfaces and high-quality audio output. This market is in the hundreds of billions.\n*   **Unified Communications & Collaboration (UCC):** The remote work surge has amplified the demand for seamless virtual meeting experiences, with the UCC market expected to exceed $100 billion.\n*   **Broadcasting & Content Creation:** Podcasts, video streaming, and professional audio production require pristine sound, a market segment worth billions.\n*   **Assistive Technologies:** Hearing aids and cochlear implants represent a specialized but significant market where noise reduction is paramount for quality of life.\n\nThis patent targets a fundamental requirement across these sectors: superior audio clarity. The ability to effectively control stationary background noise smoothing unlocks significant value in these multi-billion-dollar markets.\n\n**Competitive Advantages:**\n\nThis invention offers several distinct competitive advantages over existing noise reduction solutions:\n\n*   **Superior Performance:** By using a dual-LPC filter approach to derive a 'noisiness parameter,' the technology can achieve more adaptive and accurate noise smoothing, leading to clearer speech with fewer artifacts than traditional fixed or simpler adaptive methods.\n*   **Computational Efficiency:** Unlike some deep learning-based solutions that require substantial computational resources, this LPC-based approach is relatively efficient, making it suitable for real-time applications on edge devices with limited processing power.\n*   **Integration Flexibility:** The quantized and encoded noisiness parameter can be easily integrated into existing audio codecs and communication protocols as side information, minimizing disruption to current infrastructure.\n*   **Enhanced User Experience:** For end-users, the immediate benefit is a noticeable improvement in audio quality, reducing listening fatigue and enhancing communication effectiveness. This translates directly to higher customer satisfaction and brand loyalty.\n\n**Revenue Potential and Business Models:**\n\nCompanies can leverage this patent through various business models:\n\n*   **Licensing:** Licensing the technology to semiconductor manufacturers, telecommunication equipment providers, software developers, and consumer electronics brands. This could involve per-unit royalties or fixed licensing fees.\n*   **Integration Services:** Offering expertise to integrate this advanced noise smoothing capability into existing products or platforms.\n*   **Product Development:** Building and selling proprietary audio processing chips or software modules that incorporate this patent's methodology.\n*   **Subscription Services:** Enhancing existing communication or content platforms with premium audio clarity features, offered as a subscription add-on.\n\n**Strategic Positioning:**\n\nCompanies adopting the principles of this patent can strategically position themselves as leaders in audio innovation and quality. For example:\n\n*   **Telecommunication providers** can market 'HD Voice+' or 'Ultra-Clear Calling' services.\n*   **Headphone/headset manufacturers** can boast superior call quality and immersive listening experiences.\n*   **Software companies** developing virtual meeting platforms can offer best-in-class noise suppression.\n*   **Automotive OEMs** can provide safer and more enjoyable in-car communication and voice control.\n\n**ROI Projections:**\n\nThe return on investment for implementing this technology can be substantial. For telecommunication companies, improved call quality leads to reduced call handling times, fewer customer complaints, and increased subscriber retention. For consumer electronics, it translates to higher product differentiation, premium pricing potential, and stronger brand reputation. The efficiency gains in content production and the enhanced effectiveness of voice AI applications also contribute to a strong ROI through cost savings and increased user engagement.\n\nIn essence, the Method and Arrangement for Controlling Smoothing of Stationary Background Noise is not just a technical improvement; it's a strategic business enabler that can drive market leadership, foster customer loyalty, and unlock new revenue streams in the burgeoning audio technology landscape.","faqs":[{"answer":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** (US-9852739) is a patented innovation in audio signal processing. It describes a sophisticated technique designed to significantly enhance the representation of background noise during information coding, ultimately leading to clearer speech and improved overall audio quality.\n\nAt its core, this invention provides an intelligent way to manage and reduce persistent, unchanging background sounds (like a fan hum or distant traffic) without distorting the main audio, such as a person's voice. It moves beyond simple noise cancellation by precisely identifying and characterizing the specific nature of stationary noise.\n\nThis technology is crucial for modern communication systems, voice-controlled devices, and media consumption, where background noise often compromises clarity and user experience. By offering a more adaptive and artifact-free approach, it sets a new standard for audio fidelity in noisy environments.\n\nIt achieves this by determining a unique 'noisiness parameter' for inactive speech signals, which is then quantized and encoded for efficient transmission. This parameter guides how optimally noise smoothing should be applied.","question":"What is Method and Arrangement for Controlling Smoothing of Stationary Background Noise?"},{"answer":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** works through a clever, multi-step process to intelligently manage background noise. First, it continuously monitors the input audio signal to determine 'voice activity' – essentially, it detects when someone is speaking and when they are not.\n\nWhen no speech is detected (during 'inactive speech' segments), the system focuses on analyzing the background noise. This is where the core innovation lies: it determines a 'noisiness parameter' for this stationary background noise. This parameter isn't a simple volume measurement; it's derived from the ratio of prediction gains of two Linear Predictive Coder (LPC) prediction filters, each operating with a different order.\n\nThese two LPC filters act like specialized listening tools, each providing a different perspective on the noise's spectral characteristics. By comparing their 'prediction gains' (how well they can predict the signal), the system can accurately characterize the specific nature and steadiness of the background noise. This precise noisiness parameter is then quantized (converted into discrete values) and encoded for efficient transmission. This encoded information can then be used by a receiving device to apply a perfectly tailored amount of noise smoothing, ensuring maximum noise reduction without degrading the quality of any speech that follows. \n\nKeywords: noisiness parameter, LPC filters, prediction gains, voice activity detection, audio coding, signal processing, noise smoothing.","question":"How does Method and Arrangement for Controlling Smoothing of Stationary Background Noise work?"},{"answer":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** patent solves the pervasive problem of degraded audio quality and impaired speech intelligibility caused by stationary background noise in various communication and audio systems.\n\nMany conventional noise reduction techniques struggle with this challenge. They often either fail to adequately suppress persistent, unchanging background sounds (like office hums, air conditioner noise, or vehicle road noise) or introduce undesirable audio artifacts, such as 'musical noise,' robotic-sounding voices, or clipped speech. These compromises lead to listener fatigue, communication breakdowns, and a generally poor user experience.\n\nThis invention provides a solution by enabling highly adaptive and artifact-free noise management. It ensures that background noise is intelligently identified and smoothed out, allowing the desired speech signal to remain clear and natural. This is particularly critical in contexts like teleconferencing, voice assistant interactions, and mobile communications where diverse and often noisy environments are commonplace. \n\nKeywords: speech intelligibility, background noise, audio quality, noise reduction problem, communication breakdown, audio artifacts, stationary noise.","question":"What problem does Method and Arrangement for Controlling Smoothing of Stationary Background Noise solve?"},{"answer":"The patent **Method and Arrangement for Controlling Smoothing of Stationary Background Noise**, designated as US-9852739, does not list specific inventors or an assignee in the provided data. \n\nTypically, patent filings include the names of the individuals who conceived the invention (the inventors) and the entity that owns the patent rights (the assignee, often a company or research institution). The absence of this information in the provided abstract and patent data means it cannot be identified from this source.\n\nTo find the inventors and assignee, one would typically consult the full patent document from official patent databases like the USPTO or Google Patents, where this information is publicly available. These details are crucial for understanding the origin and ownership of the intellectual property. \n\nKeywords: patent inventors, patent assignee, US-9852739, patent ownership, intellectual property.","question":"Who invented Method and Arrangement for Controlling Smoothing of Stationary Background Noise?"},{"answer":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** offers several significant benefits that enhance audio quality and user experience across various applications:\n\n1.  **Superior Speech Clarity:** The primary benefit is a dramatic improvement in speech intelligibility, as stationary background noise is effectively suppressed without compromising the naturalness or clarity of the speaker's voice.\n2.  **Reduced Audio Artifacts:** Unlike many traditional noise reduction methods that can introduce 'musical noise' or robotic-sounding speech, this adaptive approach minimizes such undesirable artifacts, leading to a more pleasant listening experience.\n3.  **Adaptive Performance:** The technology intelligently adapts to different types and levels of stationary background noise, ensuring consistent high-quality audio performance across diverse and dynamic environments.\n4.  **Enhanced User Experience:** For end-users, this translates to less listening fatigue during calls, more reliable interactions with voice-controlled devices, and a generally more engaging audio experience in media consumption.\n5.  **Efficient Transmission:** By quantizing and encoding a precise 'noisiness parameter,' the system enables efficient communication of noise characteristics, allowing for optimal noise smoothing at the receiving end without excessive bandwidth consumption.\n\nThese benefits collectively position the invention as a key enabler for next-generation audio communication and processing. \n\nKeywords: audio clarity, speech intelligibility, noise reduction benefits, artifact-free audio, adaptive noise control, enhanced user experience, efficient audio transmission.","question":"What are the key benefits of Method and Arrangement for Controlling Smoothing of Stationary Background Noise?"},{"answer":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** distinguishes itself from prior art through its innovative approach to characterizing and controlling stationary background noise. Most prior art methods, such as basic spectral subtraction or simpler adaptive filters, often rely on less sophisticated noise estimation techniques.\n\nMany traditional systems either use a single, general noise model or make estimations based on energy levels, which can be prone to errors and lead to artifacts like 'musical noise' or over-smoothing of speech. Some advanced methods, like deep learning-based noise reduction, offer high performance but often come with significant computational overhead and require extensive training data, limiting their real-time application on resource-constrained devices.\n\nThis patent's key differentiation lies in its unique 'noisiness parameter' determination. Instead of a single, broad assessment, it uses the ratio of prediction gains from *two Linear Predictive Coder (LPC) prediction filters with different orders*. This dual-filter analysis provides a much more granular and robust fingerprint of the stationary noise's spectral characteristics and predictability. By understanding the noise at different levels of detail, the system can apply highly precise and adaptive smoothing, minimizing distortion to speech while maximizing noise suppression. Furthermore, the explicit quantization and encoding of this parameter for transmission allow for intelligent, informed noise control throughout the audio communication chain, a significant advancement over local, often less accurate, noise estimation in prior art. \n\nKeywords: prior art comparison, noise reduction differentiation, LPC filters, prediction gains, adaptive noise control, audio processing innovation, artifact reduction.","question":"How is Method and Arrangement for Controlling Smoothing of Stationary Background Noise different from prior art?"},{"answer":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** patent is poised to significantly impact a wide array of industries that rely heavily on clear and high-quality audio. Its ability to intelligently manage stationary background noise makes it a foundational technology for numerous applications.\n\n**Telecommunications:** This includes mobile voice services, VoIP, and unified communications platforms. The patent will enable clearer calls, reduce communication fatigue, and improve overall customer satisfaction.\n\n**Consumer Electronics:** Devices such as smartphones, smart speakers, headphones, and earbuds will benefit from enhanced voice clarity for calls, voice commands, and media consumption. Automotive infotainment systems will also see improvements in hands-free communication.\n\n**Enterprise Collaboration & Remote Work:** Video conferencing and virtual meeting platforms will deliver more productive and less distracting experiences by effectively suppressing office hums, keyboard clicks, and other ambient noises.\n\n**Broadcasting & Content Creation:** Podcasters, live streamers, and professional audio producers can achieve cleaner recordings and broadcasts, reducing the need for extensive post-production noise removal.\n\n**Assistive Technologies:** Hearing aids and cochlear implants can integrate this adaptive noise smoothing to provide individuals with hearing impairments a more natural and less fatiguing listening experience in complex auditory environments.\n\nThese industries will experience a transformation in user experience and operational efficiency, driven by the superior audio clarity enabled by this invention. \n\nKeywords: industry impact, telecommunications, consumer electronics, voice AI, enterprise collaboration, broadcasting, assistive technologies, audio technology market.","question":"What industries will Method and Arrangement for Controlling Smoothing of Stationary Background Noise impact?"},{"answer":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** patent, identified by the number US-9852739, has specific dates associated with its lifecycle within the patent office.\n\nThe **Filing Date** for this patent was **2016-02-09**. This is the date when the patent application was officially submitted to the patent office, marking the beginning of the examination process and establishing priority for the invention.\n\nThe **Publication Date** for this patent was **2017-12-26**. This is the date when the patent document was formally published, making its details publicly accessible. While the term 'granted' is often used interchangeably with 'published' in general conversation, the publication date indicates when the application became public, not necessarily when the patent was officially issued as a granted patent. However, for utility patents in the US, the publication date often coincides with the grant date or occurs shortly before it if the patent is granted. The provided data indicates the publication date.\n\nThese dates are important for understanding the timeline of the invention's development and its entry into the public domain. \n\nKeywords: patent filing date, patent publication date, US-9852739, patent timeline, intellectual property dates.","question":"When was Method and Arrangement for Controlling Smoothing of Stationary Background Noise filed/granted?"},{"answer":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** patent offers a wide range of commercial applications due to its ability to deliver superior audio clarity in diverse environments. This makes it highly valuable across numerous product categories and service offerings.\n\n**Telecommunications Products and Services:** Mobile phones, VoIP services, and landline communication systems can integrate this technology to offer premium call quality, reducing background noise for both callers. This can be a key differentiator for service providers.\n\n**Unified Communications and Collaboration (UCC) Platforms:** Software and hardware for virtual meetings (e.g., Zoom, Microsoft Teams, dedicated conference systems) can use this patent to significantly improve audio for remote workers and corporate environments, making virtual interactions more productive and less fatiguing.\n\n**Voice-Controlled Devices and AI:** Smart speakers, voice assistants, and other IoT devices rely on accurate voice recognition. This patent can make these devices more reliable by ensuring commands are understood clearly, even in noisy home or public settings.\n\n**Consumer Audio Devices:** High-end headphones, earbuds, and soundbars can leverage this technology to enhance both communication (e.g., clearer calls) and media consumption (e.g., cleaner audio streams) for users.\n\n**Automotive Industry:** In-car communication systems, hands-free calling, and voice navigation can benefit from better noise suppression, improving safety and user experience amidst road noise and engine sounds.\n\n**Broadcasting and Professional Audio Equipment:** Microphones, mixers, and recording software can incorporate this innovation to capture cleaner audio, reducing the need for extensive post-production noise removal in podcasts, live broadcasts, and studio recordings.\n\n**Assistive Listening Devices:** Hearing aids and cochlear implants can integrate this adaptive noise smoothing to provide a more comfortable and effective listening experience for individuals in noisy social situations. \n\nKeywords: commercial applications, telecommunications, voice assistants, UCC platforms, consumer electronics, automotive audio, professional audio, assistive listening, patent commercialization.","question":"What are the commercial applications of Method and Arrangement for Controlling Smoothing of Stationary Background Noise?"},{"answer":"The **Method and Arrangement for Controlling Smoothing of Stationary Background Noise** patent lays a robust foundation for numerous future developments in audio technology. Its core principle of intelligently characterizing and controlling noise smoothing can be extended and integrated with emerging technologies.\n\nOne significant area of future development is **integration with advanced AI and Machine Learning (ML)**. While the patent itself uses an LPC-based approach, the 'noisiness parameter' could serve as a powerful feature input for ML models, enabling even more sophisticated and context-aware noise suppression. ML could learn to dynamically adjust the LPC filter orders or the quantization scheme based on real-time environmental conditions, leading to hyper-personalized noise profiles.\n\nAnother direction is **real-time adaptation to non-stationary noise**. While the patent primarily focuses on stationary noise, its principles could be expanded to identify and smooth out transient or rapidly changing background sounds more effectively by incorporating additional dynamic features into the noisiness parameter determination.\n\nWe can also anticipate **deeper integration into audio codecs and communication protocols**, potentially becoming a standard component for next-generation 'Ultra HD Voice' or 'Immersive Audio' standards. This would ensure ubiquitous high-quality audio across all digital communication.\n\nFurthermore, future developments might include **spatial audio applications**. By combining the noisiness parameter with multi-microphone arrays, systems could not only suppress noise but also intelligently enhance specific sound sources within a 3D acoustic environment, creating truly immersive and personalized auditory experiences in augmented and virtual reality. The potential for proactive noise management, where devices anticipate and mitigate noise before it becomes disruptive, also represents an exciting future frontier. \n\nKeywords: future audio tech, AI noise reduction, machine learning integration, non-stationary noise, audio codecs, spatial audio, personalized audio, patent development.","question":"What are the future developments expected for Method and Arrangement for Controlling Smoothing of Stationary Background Noise?"}],"topics":["Method and Arrangement for Controlling Smoothing of Stationary Background Noise","US-9852739","patent","audio clarity","noise reduction","pervasive","nature","stationary"],"tech_cluster":null},"seo":{"title":"Method and Arrangement for Controlling Smoothing of Stationary Background Noise - US-9852739","description":"Discover the Method and Arrangement for Controlling Smoothing of Stationary Background Noise patent (US-9852739) for superior audio clarity. Learn how dual-LPC filters intelligently reduce background noise.","keywords":["Method and Arrangement for Controlling Smoothing of Stationary Background Noise","US-9852739","patent","audio clarity","noise reduction","speech processing","LPC filters","background noise smoothing","voice activity detection","audio enhancement","signal processing","telecommunications audio","patent analysis"]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9852739","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9852739","citation_suggestion":"Patentable. \"Method and arrangement for controlling smoothing of stationary background noise\" (US-9852739). https://patentable.app/patents/US-9852739","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9852739","json":"https://patentable.app/api/llm-context/US-9852739","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T12:19:15.493Z"}