{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9852740","patent":{"patent_number":"US-9852740","title":"Method for speech coding, method for speech decoding and their apparatuses","assignee":null,"inventors":[],"filing_date":"2016-02-12T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L","G10L"],"num_claims":14,"abstract":"A high quality speech is reproduced with a small data amount in speech coding and decoding for performing compression coding and decoding of a speech signal to a digital signal. In speech coding method according to a code-excited linear prediction (CELP) speech coding, a noise level of a speech in a concerning coding period is evaluated by using a code or coding result of at least one of spectrum information, power information, and pitch information, and various excitation codebooks are used based on an evaluation result."},"analysis":{"summary":"The patent \"Method for Speech Coding, Method for Speech Decoding and Their Apparatuses\" (US-9852740) introduces a groundbreaking method for achieving high-quality speech reproduction with significantly reduced data amounts in digital speech coding and decoding processes. The core innovation lies within the Code-Excited Linear Prediction (CELP) framework, a widely used speech compression technique.\n\nThe primary problem this invention solves is the persistent challenge of maintaining speech clarity and naturalness in varying noise environments while simultaneously minimizing bandwidth consumption. Traditional CELP systems often struggle to adapt efficiently to dynamic acoustic conditions, leading to either compromised audio quality or inefficient data usage.\n\nThis patent's key technical approach involves an intelligent, adaptive noise evaluation. During the speech coding process, the system actively assesses the noise level of the speech within a specific coding period. This evaluation is performed by analyzing critical speech parameters, including spectrum information, power information, and pitch information. Based on the precise results of this real-time noise assessment, the system then dynamically selects and utilizes various excitation codebooks. This adaptive selection of codebooks ensures that the most appropriate and efficient coding strategy is applied for the current acoustic context, optimizing both quality and data efficiency.\n\nThe business value and applications are substantial. For telecommunications and Voice over IP (VoIP) providers, this means delivering clearer calls with less bandwidth, improving customer satisfaction and reducing operational costs. In the realm of voice-controlled devices and IoT, it enables more accurate and robust voice recognition in noisy real-world settings. Streaming services can offer higher fidelity audio with less buffering, enhancing user experience.\n\nThis innovation taps into a vast market opportunity within digital communication, consumer electronics, and enterprise solutions where efficient, high-quality voice transmission is paramount. The ability to dynamically adapt to noise and optimize data usage provides a significant competitive advantage, paving the way for next-generation audio products and services.","layman_explanation":"### What Problem Does Method for Speech Coding, Method for Speech Decoding and Their Apparatuses Solve?\nImagine you're trying to have a clear phone conversation, but you're in a busy airport or a bustling coffee shop. The background noise makes it incredibly difficult to hear and be heard. This is a common challenge in digital communication: how do you send someone's voice clearly and naturally over the internet or a mobile network without using a huge amount of data, especially when there's a lot of background noise? Existing technologies often force a trade-off: either you get decent quality but consume a lot of data, or you save data but your voice sounds muffled or distorted. This patent, \"Method for Speech Coding, Method for Speech Decoding and Their Apparatuses,\" directly addresses this dilemma, aiming to deliver the best of both worlds: high-quality speech with minimal data usage, regardless of the surrounding noise.\n\n### How Does It Work?\nThink of your voice as a complex piece of music. When you speak, your phone needs to turn that music into a digital message (code it) and send it. The person on the other end then needs their phone to turn that message back into music (decode it). The magic of this patent is how it handles the 'noise' in your music. Instead of just trying to squish your voice into a tiny file blindly, this technology acts like a smart sound engineer. It first listens to your voice and its surroundings, figuring out how much background noise there is. It does this by analyzing key characteristics of your voice, like its tone (pitch), how loud it is (power), and its overall sound profile (spectrum). \n\nOnce it understands the noise level, it doesn't just use one standard way to compress your voice. Instead, it has access to a whole library of 'special coding recipes' – referred to as 'excitation codebooks.' If it detects a lot of background noise, it picks a recipe that's specifically designed to make your voice stand out clearly in a noisy environment. If it's a quiet setting, it picks a recipe that ensures your voice sounds incredibly natural and rich. This adaptive, intelligent selection of the best coding recipe allows the system to be much more efficient: it sends only the most important parts of your voice, tailored to the specific noise conditions, ensuring clarity without wasting data.\n\n### Why Does This Matter?\nThis innovation is a big deal for several reasons. Firstly, for businesses that rely on voice communication – like telecommunication companies, VoIP providers, and call centers – it means happier customers due to consistently clearer calls. It also means significant cost savings by reducing the amount of data (bandwidth) needed to maintain high-quality service. Secondly, for the booming market of smart devices and voice assistants, this technology makes them much more reliable. Imagine telling your smart speaker to play music, and it understands you perfectly, even if the kids are playing loudly in the background. This enhances user experience and drives adoption.\n\nFrom an investment perspective, companies that integrate this patent can gain a significant competitive advantage. They can offer superior products and services that stand out in terms of audio quality and operational efficiency. It's about future-proofing communication infrastructure and device capabilities in an increasingly voice-driven world. The return on investment comes from improved customer satisfaction, reduced operating expenses, and the ability to capture new market segments that demand robust, high-fidelity audio.\n\n### What's Next?\nThis patent paves the way for even more sophisticated and context-aware audio technologies. We could see future applications where communication systems automatically adjust to your activity (e.g., driving, walking, in a meeting) to optimize voice quality. It also has implications for augmented and virtual reality, where immersive, clear audio is crucial. As our lives become more integrated with digital voice interfaces, technologies like Method for Speech Coding, Method for Speech Decoding and Their Apparatuses will be fundamental to ensuring seamless, high-quality interactions across all platforms. Expect to see widespread adoption of such adaptive coding techniques in the next wave of communication and smart device innovations.","technical_analysis":"The patent \"Method for Speech Coding, Method for Speech Decoding and Their Apparatuses\" (US-9852740) outlines a sophisticated enhancement to Code-Excited Linear Prediction (CELP) speech coding, designed to achieve superior speech quality at lower bitrates, particularly in challenging acoustic environments. At its core, this innovation addresses the limitations of static codebook selection in conventional CELP systems.\n\n**Technical Architecture and Algorithm Specifics:**\nTraditional CELP codecs operate by analyzing an input speech signal to extract linear prediction (LP) coefficients, which model the vocal tract. The residual signal, after LP filtering, is then represented by an 'excitation signal' chosen from a codebook, along with a gain factor. The encoder searches the codebook for the entry that, when passed through the LP synthesis filter, produces speech closest to the original in a perceptually weighted domain. The LP coefficients, codebook index, and gain are then transmitted.\n\nThis patent introduces a critical adaptive layer to this process. The system includes:\n\n1.  **Noise Level Evaluation Module:** Prior to or concurrently with the standard CELP analysis, a module evaluates the noise level within the current speech coding period. The abstract specifies that this evaluation utilizes 'a code or coding result of at least one of spectrum information, power information, and pitch information.'\n    *   **Spectrum Information:** Analysis of the spectral envelope and fine structure can indicate the presence and type of noise. For instance, a flatter spectrum or the absence of distinct formants might suggest broadband noise.\n    *   **Power Information:** The overall energy level of the speech segment, combined with background noise estimation, can help determine the Signal-to-Noise Ratio (SNR).\n    *   **Pitch Information:** The regularity and strength of the pitch contour are strong indicators of voiced speech. Degradation in pitch correlation can signify increased noise or unvoiced segments. The 'coding result' aspect implies that features already computed for other CELP modules (e.g., LPC analysis for spectrum, autocorrelation for pitch) can be reused for noise estimation, minimizing computational overhead.\n\n2.  **Adaptive Excitation Codebook Selection:** Based on the output of the Noise Level Evaluation Module, the system dynamically selects from 'various excitation codebooks'. This is a significant departure from static codebook approaches. Instead of a single, general-purpose codebook, the system likely maintains a library of specialized codebooks, each optimized for different noise conditions or speech characteristics:\n    *   **Clean Speech Codebooks:** May contain finer quantization steps or more intricate patterns suitable for pristine speech, preserving subtle nuances.\n    *   **Noisy Speech Codebooks:** Could be designed to be more robust against specific types of noise (e.g., stationary, non-stationary) or to focus on perceptually dominant speech components, effectively masking noise artifacts.\n    *   The selection logic would map the estimated noise level (or SNR) to the most appropriate codebook. This mapping could be rule-based, trained via machine learning, or determined by a look-up table.\n\n**Implementation Details:**\nAt the encoder, after LP analysis, the noise level is assessed. The selected codebook's index, along with the LP coefficients and gain, is then transmitted. The decoder, upon receiving these parameters, uses the codebook index to select the identical codebook from its local library, reconstructs the excitation signal, and passes it through the LP synthesis filter to generate the output speech.\n\n**Performance Characteristics:**\nThis adaptive approach offers several performance advantages:\n*   **Improved Perceptual Quality:** By matching the codebook to the acoustic environment, the reconstructed speech retains higher fidelity and naturalness, with fewer artifacts, especially in noisy conditions.\n*   **Bitrate Efficiency:** Optimal codebook selection means that bits are used more effectively. Redundant information or noise components are not over-encoded, allowing for high quality at lower bitrates than a static system would achieve under varying conditions.\n*   **Robustness:** The system becomes inherently more robust to environmental changes, making it suitable for real-world applications where acoustic conditions are unpredictable.\n\n**Integration Patterns:**\nThis innovation is an enhancement to existing CELP-based codecs. It can be integrated into current communication systems (e.g., VoIP clients, mobile telephony standards) as an optimized CELP variant. Its modular nature suggests it could be implemented as a pre-processing or internal module within existing speech coding pipelines, requiring updates to codebook management and selection logic.\n\n**Code-Level Implications:**\nDevelopers would need to implement:\n*   Feature extraction routines for spectrum, power, and pitch.\n*   A noise estimation algorithm based on these features.\n*   A codebook library and a selection mechanism (e.g., switch-case, hash map, or a trained model).\n*   Synchronization logic to transmit the selected codebook identifier to the decoder.\n\nIn essence, Method for Speech Coding, Method for Speech Decoding and Their Apparatuses provides a more intelligent and context-aware speech compression, moving beyond static models to dynamically adapt to the complex realities of real-world audio, promising a significant leap in digital voice communication quality and efficiency.","business_analysis":"The patent \"Method for Speech Coding, Method for Speech Decoding and Their Apparatuses\" (US-9852740) presents a significant commercial opportunity by addressing a critical pain point in digital communication: delivering high-quality speech with maximum data efficiency across diverse environments. This innovation is poised to impact multiple industries, offering substantial market advantages and revenue potential.\n\n**Market Opportunity Size:**\nThe global market for speech and voice recognition, which heavily relies on underlying speech coding technologies, is projected to reach hundreds of billions of dollars in the coming years. This includes telecommunications (mobile and VoIP), smart home devices, automotive infotainment, gaming, virtual reality, and enterprise communication solutions. Any sector where human voice is transmitted or processed digitally stands to benefit from improved quality and efficiency. The ability of this patent to enhance both aspects simultaneously taps into a broad and rapidly expanding market.\n\n**Competitive Advantages:**\nThis technology offers a clear competitive edge:\n1.  **Superior User Experience:** In an increasingly crowded market, audio quality is a key differentiator. Products and services leveraging this patent can offer noticeably clearer calls and more natural voice interactions, leading to higher customer satisfaction and loyalty.\n2.  **Reduced Operational Costs:** By achieving high quality with a smaller data footprint, telecommunication providers, cloud communication platforms, and streaming services can significantly reduce bandwidth costs and infrastructure requirements. This translates directly to improved profit margins and scalability.\n3.  **Enhanced Device Performance:** For IoT devices and voice assistants, this means more reliable voice command recognition in noisy real-world settings, reducing errors and improving user trust. This makes devices more robust and competitive.\n4.  **Future-Proofing:** As 5G and future networks emphasize low latency and high data throughput for rich media, this patent ensures that voice remains a high-quality, efficient component of the overall digital experience, even as other media types become more demanding.\n\n**Revenue Potential and Business Models:**\nRevenue can be generated through several business models:\n*   **Licensing:** Technology companies (e.g., chip manufacturers, software developers, telecom equipment providers) can license the patent for integration into their products and services.\n*   **Product Development:** Companies can develop and sell enhanced codecs, software development kits (SDKs), or complete communication platforms that incorporate this adaptive speech coding method.\n*   **Service Enhancement:** VoIP providers, mobile carriers, and unified communications platforms can integrate this technology to offer premium-tier services with guaranteed high-definition audio quality, justifying higher subscription fees or attracting more users.\n*   **Embedded Solutions:** For automotive, aerospace, or industrial applications, the patent could be embedded into specialized communication modules, sold as high-value components.\n\n**Strategic Positioning:**\nCompanies adopting this patent can strategically position themselves as leaders in 'Intelligent Audio,' 'Adaptive Communication,' or 'High-Fidelity, Low-Bandwidth Solutions.' This allows them to differentiate from competitors relying on older, less adaptive speech coding methods. It also enables them to enter new markets or expand existing ones by solving persistent audio quality challenges.\n\n**ROI Projections:**\nWhile specific ROI depends on implementation and market penetration, the cost savings from reduced bandwidth and improved customer retention/acquisition can be substantial. A telecom provider, for instance, could see millions in annual savings from optimized network usage. A smart device manufacturer could experience a significant boost in sales due to superior voice interaction capabilities. The investment in licensing or developing around this patent is likely to yield strong returns by enhancing core product offerings and reducing operational overhead.\n\nIn conclusion, Method for Speech Coding, Method for Speech Decoding and Their Apparatuses is not just a technical improvement; it's a strategic asset that can unlock new market opportunities, drive competitive advantage, and generate significant revenue across the digital audio ecosystem.","faqs":[{"answer":"Method for Speech Coding, Method for Speech Decoding and Their Apparatuses (US-9852740) is a patent for an advanced system designed to improve the quality and efficiency of digital speech communication. At its core, this innovation focuses on how speech signals are compressed into digital data (coding) and then converted back into audible speech (decoding).\n\nThe patent specifically enhances Code-Excited Linear Prediction (CELP), a widely used speech compression technique. It introduces a smart, adaptive mechanism that allows the system to deliver high-quality speech even when operating with a small amount of data, a critical capability for modern telecommunications and digital audio applications.\n\nThis technology is about making your digital voice interactions clearer and more reliable, regardless of the surrounding acoustic environment. It represents a significant step forward in balancing the trade-offs between audio fidelity and data bandwidth.","question":"What is Method for Speech Coding, Method for Speech Decoding and Their Apparatuses?"},{"answer":"The Method for Speech Coding, Method for Speech Decoding and Their Apparatuses works by intelligently adapting its speech compression strategy to the prevailing noise conditions. During the speech coding process, the system actively evaluates the level of background noise present in the speech signal.\n\nThis evaluation is not a simple guess; it's a sophisticated analysis that uses key characteristics of the speech, such as its spectrum information (the overall frequency content), power information (its loudness), and pitch information (the fundamental frequency of the voice). By analyzing these parameters, the system gains a clear understanding of the acoustic environment.\n\nCrucially, based on this real-time noise assessment, the patent then directs the system to select and use 'various excitation codebooks'. These are essentially different optimized 'recipes' for compressing speech. If it detects a lot of noise, it chooses a codebook specifically designed to make speech clear in noisy settings. If it's quiet, it picks one that preserves the naturalness and richness of the voice. This adaptive selection ensures optimal quality and data efficiency.","question":"How does Method for Speech Coding, Method for Speech Decoding and Their Apparatuses work?"},{"answer":"The Method for Speech Coding, Method for Speech Decoding and Their Apparatuses solves the long-standing problem of achieving consistently high-quality speech reproduction with minimal data usage, especially in the presence of varying background noise. Traditional speech coding methods often face a dilemma: either they prioritize high fidelity but consume a lot of bandwidth, or they prioritize low bandwidth but compromise on audio quality.\n\nThis patent directly addresses the challenge of dynamic acoustic environments. In real-world scenarios, the noise level around a speaker constantly changes (e.g., quiet room, busy street, car interior). Older systems struggle to adapt efficiently to these changes, leading to muffled calls, artifacts, or inefficient data transmission.\n\nBy intelligently evaluating noise and adaptively adjusting its coding strategy, this innovation ensures that speech remains clear and natural, regardless of the environment, while simultaneously keeping data consumption low. This is a critical solution for modern digital communication, from mobile calls to voice-controlled devices.","question":"What problem does Method for Speech Coding, Method for Speech Decoding and Their Apparatuses solve?"},{"answer":"The patent data available (US-9852740) does not specify the inventors or assignee. Often, patents are filed by corporations, and the inventors are individuals employed by that corporation. Without this information explicitly provided, the specific individuals or company responsible for the invention of Method for Speech Coding, Method for Speech Decoding and Their Apparatuses cannot be identified here.\n\nHowever, the nature of the invention, focusing on advanced speech coding techniques within the Code-Excited Linear Prediction (CELP) framework, suggests it likely originated from research and development efforts within a major telecommunications company, a digital signal processing firm, or an academic institution specializing in audio technology. These organizations are typically at the forefront of innovating in areas like speech coding and decoding to enhance digital communication.\n\nTo find the specific inventors and assignee, one would typically refer to the full patent document filed with the patent office, which contains these details. This information is crucial for understanding the ownership and origin of the Method for Speech Coding, Method for Speech Decoding and Their Apparatuses technology.","question":"Who invented Method for Speech Coding, Method for Speech Decoding and Their Apparatuses?"},{"answer":"The Method for Speech Coding, Method for Speech Decoding and Their Apparatuses offers several key benefits that are set to transform digital audio communication:\n\n1.  **Superior Speech Quality:** It delivers consistently high-quality, clear, and natural-sounding speech, even in noisy or challenging acoustic environments. This significantly improves the user experience for calls, conferences, and voice interactions.\n2.  **Reduced Data Consumption:** The adaptive nature of the technology allows it to achieve this high quality with a smaller amount of data compared to less adaptive methods. This translates to lower bandwidth usage, cost savings for service providers, and potentially less data usage for end-users.\n3.  **Enhanced Robustness:** The system is inherently more resilient to varying background noise types and levels. This makes devices and communication services more reliable in real-world conditions, from a quiet room to a bustling city street.\n4.  **Improved Device Performance:** For voice-controlled devices like smart speakers or car infotainment systems, this patent enables more accurate voice recognition, reducing errors and enhancing the overall user interaction. These benefits make Method for Speech Coding, Method for Speech Decoding and Their Apparatuses a powerful advancement.","question":"What are the key benefits of Method for Speech Coding, Method for Speech Decoding and Their Apparatuses?"},{"answer":"The Method for Speech Coding, Method for Speech Decoding and Their Apparatuses differentiates itself from prior art (existing technologies) primarily through its intelligent and integrated adaptive approach to excitation codebook selection within the CELP framework.\n\nPrior art CELP codecs often use fixed or semi-fixed excitation codebooks for a given bitrate or mode. While these are efficient for specific, controlled conditions, they struggle when the acoustic environment changes. For instance, a codebook optimized for clean speech performs poorly in noise, and vice versa. Some prior solutions use external noise reduction pre-processing, but this can introduce artifacts or distort speech before coding.\n\nThis patent's innovation lies in its *dynamic* evaluation of the noise level using spectrum, power, and pitch information, and then *adaptively selecting* from 'various excitation codebooks' based on that real-time assessment. This means the system doesn't just apply a generic compression; it customizes the compression strategy to the exact noise conditions. This integrated, context-aware adaptation allows Method for Speech Coding, Method for Speech Decoding and Their Apparatuses to achieve superior quality and efficiency without the compromises inherent in less adaptive or pre-processing-reliant prior art systems.","question":"How is Method for Speech Coding, Method for Speech Decoding and Their Apparatuses different from prior art?"},{"answer":"The Method for Speech Coding, Method for Speech Decoding and Their Apparatuses is poised to impact a wide array of industries that rely on digital voice communication and processing:\n\n1.  **Telecommunications:** Mobile network operators, Voice over IP (VoIP) providers, and unified communication platforms will benefit from clearer calls, reduced bandwidth costs, and enhanced customer satisfaction.\n2.  **Consumer Electronics:** Manufacturers of smartphones, smart speakers, headphones with active noise cancellation, and other audio devices can integrate this technology for superior voice quality and more reliable voice command recognition.\n3.  **Automotive:** In-car communication systems, infotainment units, and voice control features can overcome cabin noise and road noise more effectively, improving safety and user experience.\n4.  **Streaming & Media:** Audio streaming services and online gaming platforms can deliver higher fidelity voice chat and content with greater data efficiency and less buffering.\n5.  **Artificial Intelligence & IoT:** Developers of voice assistants, smart home devices, and other Internet of Things applications can achieve higher accuracy in speech recognition, making their products more robust in real-world, noisy environments. The adaptability of Method for Speech Coding, Method for Speech Decoding and Their Apparatuses makes it relevant across these diverse sectors.","question":"What industries will Method for Speech Coding, Method for Speech Decoding and Their Apparatuses impact?"},{"answer":"The patent \"Method for Speech Coding, Method for Speech Decoding and Their Apparatuses\" (US-9852740) was filed on **February 12, 2016**. It was subsequently published and granted on **December 26, 2017**.\n\nThe filing date marks when the application was first submitted to the patent office, establishing its priority date. The publication date, usually close to the grant date for utility patents in the US, indicates when the full details of the invention became publicly available. These dates are crucial for understanding the patent's legal standing, its place in the timeline of technological development, and its remaining term of protection.\n\nFor Method for Speech Coding, Method for Speech Decoding and Their Apparatuses, its relatively recent grant date means it holds significant potential for commercialization and widespread adoption in current and future digital audio technologies.","question":"When was Method for Speech Coding, Method for Speech Decoding and Their Apparatuses filed/granted?"},{"answer":"The commercial applications of Method for Speech Coding, Method for Speech Decoding and Their Apparatuses are extensive, spanning any sector where efficient, high-quality digital voice communication is critical:\n\n1.  **Enhanced Telephony & VoIP Services:** Providers can offer premium 'HD Voice' services with superior clarity, even in noisy environments, leading to increased customer satisfaction and competitive differentiation. This includes mobile calls, business conferencing, and consumer VoIP applications.\n2.  **Smart Device & Voice Assistant Improvement:** Integration into smart speakers, smartphones, smart home hubs, and other IoT devices will significantly boost the accuracy and reliability of voice commands and interactions, making these devices more user-friendly and functional in real-world, often noisy, settings.\n3.  **Automotive Communication Systems:** The technology can be applied to in-car communication, hands-free calling, and voice-controlled infotainment, overcoming challenges posed by road noise and engine sounds for a safer and more enjoyable driving experience.\n4.  **Gaming and Virtual/Augmented Reality:** For multiplayer gaming and immersive VR/AR experiences, Method for Speech Coding, Method for Speech Decoding and Their Apparatuses can deliver crystal-clear in-game voice chat and realistic spatial audio, enhancing immersion and team coordination.\n5.  **Professional Audio & Broadcasting:** Applications in remote broadcasting, live streaming, and professional conferencing can benefit from robust, high-fidelity audio transmission under varying conditions, ensuring clear communication for critical operations. These diverse applications highlight the broad commercial potential of this adaptive speech coding patent.","question":"What are the commercial applications of Method for Speech Coding, Method for Speech Decoding and Their Apparatuses?"},{"answer":"The Method for Speech Coding, Method for Speech Decoding and Their Apparatuses lays a strong foundation for several exciting future developments in digital audio technology:\n\n1.  **More Granular Adaptivity:** Future iterations could involve even finer-grained noise level classifications and a larger, more specialized library of excitation codebooks. This would allow for hyper-optimized compression strategies tailored to extremely specific acoustic scenarios.\n2.  **Integration with Machine Learning and AI:** Deep learning models could be employed for highly accurate, real-time noise estimation and even for dynamically generating or synthesizing optimal codebooks on the fly, moving beyond pre-defined libraries. This could lead to self-learning audio codecs.\n3.  **Multi-modal Contextual Awareness:** Beyond just audio cues, future systems might integrate information from other sensors (e.g., visual data from cameras, location data from GPS, accelerometer data) to gain an even richer understanding of the user's environment and context. This would allow for even more intelligent adaptation.\n4.  **Personalized Audio Profiles:** The technology could evolve to learn individual speaker characteristics, accents, or even emotional states, adapting the coding to deliver a more personalized and perceptually optimized listening experience for each user.\n5.  **Energy Efficiency for Edge Devices:** Further optimization for low power consumption will be crucial, enabling the deployment of this advanced coding on tiny, battery-powered IoT devices without sacrificing battery life. The principles of Method for Speech Coding, Method for Speech Decoding and Their Apparatuses are thus expected to drive the next wave of intelligent, efficient, and immersive audio experiences.","question":"What are the future developments expected for Method for Speech Coding, Method for Speech Decoding and Their Apparatuses?"}],"topics":["speech coding","speech decoding","CELP","code-excited linear prediction","audio compression","landscape","digital","speech"],"tech_cluster":null},"seo":{"title":"Speech Coding & Decoding - Method for Speech Coding, Method for Speech Decoding and Their Apparatuses US-9852740","description":"Discover Method for Speech Coding, Method for Speech Decoding and Their Apparatuses: high-quality speech with less data using adaptive CELP coding and noise evaluation.","keywords":["speech coding","speech decoding","CELP","code-excited linear prediction","audio compression","noise reduction","digital signal processing","VOIP technology","patent US-9852740","adaptive codebook","high quality speech","small data amount","spectrum information","pitch information","power information"]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9852740","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-9852740","citation_suggestion":"Patentable. \"Method for speech coding, method for speech decoding and their apparatuses\" (US-9852740). https://patentable.app/patents/US-9852740","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9852740","json":"https://patentable.app/api/llm-context/US-9852740","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-06-06T06:36:52.873Z"}