Headnote
Received 03.04.2025, received in revised form 05.05.2025, accepted 15.07.2025
Abstract. The Adaptive Differential Pulse Code Modulation (ADPCM) has been standardized by the International Telecommunication Union (ITU) due to its significance and extensive applications within telecommunication networks. This paper provides a concise overview of the recent US patents related to ADPCM, covering the years 2024 to 2025. Additionally, the general architecture of ADPCM is discussed. The findings presented herein aim to inspire researchers and motivate further explorations in this domain.
Keywords: US Patents, ADPCM, applications.
Аннотация. Адаптивная дифференциально-импульсная кодовая модуляция (ADPCM) была стандартизирована Международным союзом электросвязи (МСЭ) благодаря своей значимости и широкому применению в телекоммуникационных сетях. В данной статье представлен краткий обзор последних патентов США, связанных с ADPCM, охватывающий период с 2024 по 2025 год. Кроме того, рассматривается общая архитектура ADPCM. Представленные здесь результаты призваны вдохновить исследователей и побудить их к дальнейшим изысканиям в этой области.
Ключевые слова: патенты США, ADPCM, приложения.
Introduction
The growing demand for the efficient utilization of digital communication channels has led to the development of various effective speech coding techniques. Among these is the internationally standardized Adaptive Differential Pulse Code Modulation (ADPCM), established by the International Telecommunication Union (ITU). The choice of ADPCM can be attributed to its exceptional performance, cost-effectiveness, and versatility in application when compared to other bandwidth reduction methods.
The specifications of ADPCM enable a wide range of applications within telecommunications networks, which can be classified into three main categories: applications for telephone companies, end-user applications, and the introduction of new services.
Structure of ADPCM
Fig.1 illustrates a simplified block diagram of the ADPCM codec [1, 2]. The algorithm consists of two principal components: an adaptive quantizer and an adaptive predictor. The relationship between the encoder and the decoder is also represented. The key difference is that the encoder incorporates both an adaptive quantizer (О) and its inverse (Q^-1), while the decoder exclusively features the inverse adaptive quantizer. Thus, the decoder can be viewed as a subset of the encoder, outputting r(n) instead of c(n). The adaptive predictor generates an estimate of the input signal, denoted as S(n), which is then subtracted from the input signal s(n) to produce a difference signal labeled d(n). The adaptive quantizer subsequently encodes d(n) into the codeword c(n) for transmission. Upon reception, the ADPCM decoder utilizes с(п) in an effort to reconstruct the original signal s(n). Ultimately, only r(n) can be reconstructed, which is connected to the original input signal s(n) through a specific relationship.
r(n) = sm) + e(n), ()
where
e(n) = dq) - d(n) = r(n) - sm). (2)
is the error introduced by the quantizer, and dq(n) is the output of inverse adaptive quantizer
A typical measure of the ADPCM performance is given by signal-to-noise ratio (SNR)
SNR= E[s"(n)]/E[e·(n)] = 5,7 02°, (3)
where E denotes expectation, σ2s is the power (or variance) of input signal, & o. is the power (or variance) of the error signal.
US Patents on ADPCM
This section describes briefly the recent US patents on ADPCM published from 2024 to 2025vas follows:
In [3], a method for wireless capture of real-time audio and video at a live event using a mobile computing device includes receiving a data representation of a live audio signal corresponding to the live event via a wireless network. The method also includes processing the data representation of the live audio signal into a live audio stream. The method also includes initiating a video capture corresponding to the live event. The method also includes producing, concurrent with the video capture, a shareable video corresponding to the live event based on the captured video and the live audio stream.
In [4], a hearing instruments, such as hearing aids, may improve a quality of presented audio through the use of a binaural application, such as beamforming. The binaural application may require communication between the hearing instruments so that audio from a left hearing instrument may be combined with audio from a right hearing instrument. The combining at a hearing instrument can require synchronizing audio sampled locally with sampled audio received from wireless communication. This synchronization may cause a noticeable delay of an output of the binaural application if the latency of the wireless communication is not low (e.g., a few samples of delay). Presented herein is a lowlatency communication protocol that communicates packets on a sample-by-sample basis and that compensates for delays caused by overhead protocol data transmitted with the audio data.
In [5], audio streaming devices, systems, and methods may employ adaptive differential pulse code modulation techniques providing for optimum performance even while ensuring robustness against transmission errors. One illustrative device includes: a difference element that produces a sequence of prediction error values by subtracting predicted values from audio samples; a scaling element that produces scaled error values by dividing each prediction error by a corresponding envelope estimate; a quantizer that operates on the scaled error values to produce quantized error values; a multiplier that uses the corresponding envelope estimates to produce reconstructed error values; a predictor that produces the next audio sample values based on the reconstructed error values; and an envelope estimator. The envelope estimator includes: an updater that applies a dynamic gain to the reconstructed error values to produce update values; and an integrator that combines each of the update values with the corresponding envelope estimate to produce a subsequent envelope estimate.
In [6], various arrangements for facilitating smart television content receivers in a local network are provided. In an example, a secondary television receiver receives audio data, converts the audio data into voice command data, and transmits the voice command data to a primary television receiver. In response, the primary television receiver transmits the voice command data to a voice processing server via the Internet, receives a command generated based on the voice command data, and transmits the command to the secondary television receiver. Based on the command, an operation of the secondary television receiver is controlled.
In [7], audio and video transmission device and audio and video transmission system are provided. The audio and video transmission system includes an audio and video transmission device and at least one wireless microphone transmitting device. Each of the at least one wireless microphone transmitting device is configured to send an audio signal acquired by a wireless microphone to the audio and video transmission device. The audio and video transmission device is configured to be respectively connected to the wireless microphone transmitting device and an external video acquisition device and configured to: receive the audio signal from the wireless microphone transmitting device and transmit the audio signal to the video acquisition device, obtain a mixture signal generated by the video acquisition device from the audio signal and a video signal, and process and output the mixture signal.
In [8], a packet-spreading data transmission system with anonymized endpoints facilitates enhanced fortified private communications between a plurality of arbitrary devices via a plurality of communication channels or networks. The data transmission system receives at a source endpoint device a message of arbitrary length. The message includes a destination address associated with a destination endpoint device. Both source endpoint device and the destination endpoint device are selected from a plurality of arbitrary devices. The received message are fragmented and agilely transmitted, via a plurality of communication channels, from the source endpoint device to the destination endpoint device.
In [9], techniques are described for psychoacoustic audio coding of ambisonic audio data. A device comprising a memory and one or more processors may be configured to perform the techniques. The memory may store the bitstream that includes an encoded audio object and a corresponding spatial component that defines spatial characteristics of the encoded foreground audio signal. The encoded foreground audio signal may include a coded gain and a coded shape. The one or more processors may perform a gain and shape synthesis with respect to the coded gain and the coded shape to obtain a foreground audio signal, and reconstruct, based on the foreground audio signal and the spatial component, the ambisonic audio data.
In [10], softdecision audio decoding system for preserving audio continuity in a digital wireless audio receiver is provided that deduces the likelihood of errors in a received digital signal, based on generated hard bits and softbits. The softbits may be utilized by a softaudio decoder to determine whether the digital signal should be decoded or muted. The softbits may be generated based on the detected point and a detected noise power, or by using a soft-output Viterbi algorithm. The value of the softbits may indicate confidence in the strength of the hard bit generation. The softdecision audio decoding system may infer errors and decode perceptually acceptable audio without requiring error detection, as in conventional systems, as well as have low latency and improved granularity.
In [11], an audio mixing device includes: a gain setting circuit configured to set first to n-th gains based on a command input from the outside, n being an integer of 2 or more; and a mixing circuit configured to output a mixing signal obtained by mixing two or more of first to n-th multiplication data obtained by respectively multiplying first to n-th audio data by the first to n-th gains.
In [12], as a bit stream generation method for generating a bit stream of transmission data in which a plurality of signals including at least a tactile signal is multiplexed, a signal transmission unrequired section of the tactile signal is determined and, in a case where the signal transmission unrequired section exists, the bit stream in which additional information other than the tactile signal is inserted into the signal transmission unrequired section is generated.
In [13], systems and methods include using a clustering engine to determine topics in a communication. An example system includes a user interface module that receives user input relating to a criteria to define a set of communications, wherein the criteria is at least one of a category, a score, a sentiment, an agent, an agent grouping, a speaker, a location, an event attribute, a call center, a time of communication, or a date of communication, an acoustic analysis module that analyzes the set of communications to determine one or more acoustic characteristics of one or more communications in the set of communications, and a clustering engine that analyzes words and phrases in the set of communications and the one or more acoustic characteristics, and to determine a topic of the set of communications based on at least one commonality in words, phrases, or the one or more acoustic characteristics.
In [14], a gain adjustment apparatus for use in decoding of audio that has been encoded with separate gain and shape representations includes an accuracy meter configured to estimate an accuracy measure of the shape representation, and to determine a gain correction based on the estimated accuracy measure. An envelope adjuster further included in the apparatus is configured to adjust the gain representation based on the determined gain correction.
In[15], a packet-spreading data transmission system with anonymized endpoints facilitates enhanced fortified private communications between a plurality of arbitrary devices via a plurality of communication channels or networks. The data transmission system receives at a source endpoint device a message of arbitrary length. The message includes a destination address associated with a destination endpoint device. Both source endpoint device and the destination endpoint device are selected from a plurality of arbitrary devices. The received message are fragmented and agilely transmitted, via a plurality of communication channels, from the source endpoint device to the destination endpoint device.
In [16], hearing instruments, such as hearing aids, may improve a quality of presented audio ugh the use of a binaural application, such as beamforming. The binaural application may require communication between the hearing instruments so that audio from a left hearing instrument may be combined with audio from a right hearing instrument. The combining at a hearing instrument can require synchronizing audio sampled locally with sampled audio received from wireless communication. This synchronization may cause a noticeable delay of an output of the binaural application if the latency of the wireless communication is not low (e.g., a few samples of delay). Presented herein is a lowlatency communication protocol that communicates packets on a sample-by-sample basis and that compensates for delays caused by overhead protocol data transmitted with the audio data.
Summary and Conclusion
Recent US patents on ADPCM were presented in order to show the importance and the applications of ADPCM in telecommunication networks. The general structure of the ADPCM was also presented.
Sidebar
References
References
[1] 40, 32,24,16 kb/s ADPCM, CCITT Recommendation G.726-1990.
[2] AL-Rawi M. ADPCM: US patents from 2010 to 2016. International Journal of Open Information Technologies, 2017, 5(3).
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