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Linear predictive coding

About: Linear predictive coding is a research topic. Over the lifetime, 6565 publications have been published within this topic receiving 142991 citations. The topic is also known as: Linear predictive coding, LPC.


Papers
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PatentDOI
TL;DR: In this article, an automated method for modifying a speech signal in a telephone network by applying a gain factor which is a function of the level of background noise at a given destination, and transmitting the modified speech signal to the destination was proposed.
Abstract: An automated method for modifying a speech signal in a telephone network by applying a gain factor which is a function of the level of background noise at a given destination, and transmitting the modified speech signal to the destination. The gain applied may be a function of both the background noise level and the original speech signal. Either a linear or a non-linear (e.g., compressed) amplification of the original speech signal may be performed, where a compressed amplification results in the higher level portions of the speech signal being amplified by a smaller gain factor than lower level portions. The speech signal may be separated into a plurality of subbands, each resultant subband signal being individually modified in accordance with the present invention. In this case, each subband speech signal is amplified by a gain factor based on a corresponding subband noise signal, generated by separating the background noise signal into a corresponding plurality of subbands. The individual modified subband signals may then be combined to form the resultant modified speech signal.

214 citations

Proceedings ArticleDOI
21 Apr 1997
TL;DR: This work proposes a new representational format, the modulation spectrogram, that discards much of the spectro-temporal detail in the speech signal and instead focuses on the underlying, stable structure incorporated in the low-frequency portion of the modulation spectrum distributed across critical-band-like channels.
Abstract: Understanding the human ability to reliably process and decode speech across a wide range of acoustic conditions and speaker characteristics is a fundamental challenge for current theories of speech perception. Conventional speech representations such as the sound spectrogram emphasize many spectro-temporal details that are not directly germane to the linguistic information encoded in the speech signal and which consequently do not display the perceptual stability characteristic of human listeners. We propose a new representational format, the modulation spectrogram, that discards much of the spectro-temporal detail in the speech signal and instead focuses on the underlying, stable structure incorporated in the low-frequency portion of the modulation spectrum distributed across critical-band-like channels. We describe the representation and illustrate its stability with color-mapped displays and with results from automatic speech recognition experiments.

211 citations

Journal ArticleDOI
TL;DR: A new method of processing speech degraded by reverberation based on analysis of short segments of data to enhance the regions in the speech signal having a high signal-to-reverberant component ratio (SRR).
Abstract: We propose a new method of processing speech degraded by reverberation. The method is based on analysis of short (2 ms) segments of data to enhance the regions in the speech signal having a high signal-to-reverberant component ratio (SRR). The short segment analysis shows that SRR is different in different segments of speech. The processing method involves identifying and manipulating the linear prediction residual signal in three different regions of the speech signal, namely, high SRR region, low SRR region, and only reverberation component region. A weight function is derived to modify the linear prediction residual signal. The weighted residual signal samples are used to excite a time-varying all-pole filter to obtain perceptually enhanced speech. The method is robust to noise present in the recorded speech signal. The performance is illustrated through spectrograms, subjective and objective evaluations.

210 citations

Journal ArticleDOI
TL;DR: A low-bit-rate linear predictive coder (LPC) that is based on variable-length segment quantization that is compared to that of fixed-length segments quantization and vector quantization for voice coding is presented.
Abstract: A low-bit-rate linear predictive coder (LPC) that is based on variable-length segment quantization is presented. In this vocoder, the speech spectral-parameter sequence is represented as the concatenation of variable-length spectral segments generated by linearly time-warping fixed-length code segments. Both the sequence of code segments and the segment lengths are efficiently determined using a dynamic programming procedure. This procedure minimizes the spectral distance measured between the original and the coded spectral sequence in a given interval. An iterative algorithm is developed for designing fixed-length code segments for the training spectral sequence. It updates the segment boundaries of the training spectral sequence using an a priori codebook and updates the codebook using these segment sequences. The convergence of this algorithm is discussed theoretically and experimentally. In experiments, the performance of variable-length segment quantization for voice coding is compared to that of fixed-length segment quantization and vector quantization. >

209 citations

Journal ArticleDOI
TL;DR: A new method based on the global phase characteristics of minimum phase signals for determining the instants of significant excitation in speech signals is proposed, which works well for all types of voiced speech in male as well as female speech but, in all cases, under noise-free conditions only.
Abstract: A new method for determining the instants of significant excitation in speech signals is proposed. In the paper, significant excitation refers primarily to the instant of glottal closure within a pitch period in voiced speech. The method is based on the global phase characteristics of minimum phase signals. The average slope of the unwrapped phase of the short-time Fourier transform of linear prediction residual is calculated as a function of time. Instants where the phase slope function makes a positive zero-crossing are identified as significant excitations. The method is discussed in a source-filter context of speech production. The method is not sensitive to the characteristics of the filter. The influence of the type, length, and position of the analysis window is discussed. The method works well for all types of voiced speech in male as well as female speech but, in all cases, under noise-free conditions only. >

209 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20239
202225
202126
202042
201925
201837