Topic
Speech coding
About: Speech coding is a research topic. Over the lifetime, 14245 publications have been published within this topic receiving 271964 citations.
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01 Sep 2009
TL;DR: In this paper, an active noise reduction (ANR) circuit is used to adjust the hearing compensated audio signal based on the ANR signal to produce an output audio signal, wherein the ANRs signal is generated based on output audio signals.
Abstract: A circuit includes a microphone circuit, an audio processing module, a digital audio processing module, and an active noise reduction (ANR) circuit. The microphone circuit receives acoustic vibrations and generates an audio signal therefrom. The audio processing module generates a representation of the audio signal. The digital audio processing module compensates the representation of the audio signal based on hearing compensation data to produce a hearing compensated audio signal. The ANR circuit receives the hearing compensated audio signal and an ANR signal. The ANR circuit further functions to adjust the hearing compensated audio signal based on the ANR signal to produce an output audio signal, wherein the ANR signal is generated based on the output audio signal.
65 citations
CNET1
TL;DR: In this article, a transform coding algorithm devoted to high quality audio coding at a bit rate of 64 kbps per monophonic channel is presented. But, although a complete system including framing, synchronization and error correction has been developed, only the bit rate compression algorithm is described.
Abstract: This paper presents a transform coding algorithm devoted to high quality audio coding at a bit rate of 64 kbps per monophonic channel. It enables the transmission of a high quality stereo sound through the basic access (2B channels) of ISDN. Although a complete system including framing, synchronization and error correction has been developed, only the bit rate compression algorithm is described here. A detailed analysis of the signal processing techniques such as the time/frequency transformation, the pre-echo reduction by adaptive filtering, the fast algorithm computations, etc., is provided. The use of psychoacoustical properties is also precisely reported. Finally, some subjective evaluation results and one real time implementation of the coder using the ATT DSP32C digital signal processor are presented. >
65 citations
TL;DR: By combining an interframe quantizer and a memoryless "safety-net" quantizer, it is demonstrated that the advantages of both quantization strategies can be utilized, and the performance for both noiseless and noisy channels improves.
Abstract: In linear predictive speech coding algorithms, transmission of linear predictive coding (LPC) parameters-often transformed to the line spectrum frequencies (LSF) representation-consumes a large part of the total bit rate of the coder. Typically, the LSF parameters are highly correlated from one frame to the next, and a considerable reduction in bit rate can be achieved by exploiting this interframe correlation. However, interframe coding leads to error propagation if the channel is noisy, which possibly cancels the achievable gain. In this paper, several algorithms for exploiting interframe correlation of LSF parameters are compared. Especially, performance for transmission over noisy channels is examined, and methods to improve noisy channel performance are proposed. By combining an interframe quantizer and a memoryless "safety-net" quantizer, we demonstrate that the advantages of both quantization strategies can be utilized, and the performance for both noiseless and noisy channels improves. The results indicate that the best interframe method performs as good as a memoryless quantizing scheme, with 4 bits less per frame. Subjective listening tests have been employed that verify the results from the objective measurements.
65 citations
21 Apr 1997
TL;DR: Several algorithmic changes have been introduced into G.729 which resulted in 50% drop in its complexity, enabling a DSP implementation with a complexity of about 10-12 MIPS, while meeting the terms of reference.
Abstract: This paper describes the recently adopted ITU-T Recommendation G.729 Annex A (G.729A) for encoding speech signals at 8 kbit/s with low complexity. G.729A has been selected as the standard speech coding algorithm for multimedia digital simultaneous voice and data (DSVD). G.729A is bitstream interoperable with G.729; i.e., speech coded with G.729A can be decoded with G.729, and vice versa. As G.729, it uses the conjugate structure algebraic code excited linear prediction (CS-ACELP) algorithm with 10 ms frames. However, several algorithmic changes have been introduced into G.729 which resulted in 50% drop in its complexity, enabling a DSP implementation with a complexity of about 10-12 MIPS. This paper describes the algorithmic changes which have been introduced in order to achieve the low complexity goal while meeting the terms of reference. Subjective tests have been performed by ITU-T in both the selection phase and the characterization phase and the results showed that the performance of G.729A is equivalent to both G.729 and G.726 at 32 kbit/s in most operating conditions; however, it is slightly worse in case of three tandems and in the presence of background noise. A breakdown of the complexities of both G.729 and G.729A is given at the end of the paper.
65 citations