The DOI matches its Crossref record; 10 of the 12 references it cites were found in a registry or an index.
Adaptive Predictive Coding of Speech Signals
Abstract
We describe in this paper a method for efficient encoding of speech signals, based on predictive coding. In this coding method, both the transmitter and the receiver estimate the signal's current value by linear prediction on the previously transmitted signal. The difference between this estimate and the true value of the signal is quantized, coded and transmitted to the receiver. At the receiver, the decoded difference signal is added to the predicted signal to reproduce the input speech signal. Because of the nonstationary nature of the speech signals, an adaptive linear predictor is used, which is readjusted periodically to minimize the mean-square error between the predicted and the true value of the signals. The predictive coding system was simulated on a digital computer. The predictor parameters, comprising one delay and nine other coefficients related to the signal spectrum, were readjusted every 5 milliseconds. The speech signal was sampled at a rate of 6.67 kHz, and the difference signal was quantized by a two-level quantizer with variable step size. Subjective comparisons with speech from a logarithmic PCM encoder (log-PCM) indicate that the quality of the synthesized speech signal from the predictive coding system is approximately equal to that of log-PCM speech encoded at 6 bits/sample. Preliminary studies suggest that the binary difference signal and the predictor parameters together can be transmitted at approximately 10 kilobits/second which is several times less than the bit rate required for log-PCM encoding with comparable speech quality.
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“This framework has resulted in excellent representation learning performance across domains such as computer vision [12, 33, 35], natural language [49], speech recognition [6, 58] and time-series data [39].”
From Contrastive Predictive Coding for Human Activity Recognition (2021) · cites this paper as [6]
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Metadata
- Authors
- Atal, B. S., & Schroeder, M. R.
- ORCID
- Atal, B. S.
- Venue
- Bell System Technical Journal
- Published
- 1970-10
- Volume
- 49
- Issue
- 8
- Pages
- 1973-1986
- ISSN
- 0005-8580 (ISSN-L)
- OpenAlex
- W2037034710
- Cited by
- 256
- References
- 12
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 6 · 2023: 8 · 2022: 3 · 2021: 3 · 2020: 7 · 2019: 6 · 2018: 2 · 2017: 4 · 2016: 2 · 2015: 1 · 2014: 4 · 2013: 2 · 2012: 12
- FWCI
- 9.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Bell System Technical Journal (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Signal Processing › Speech and Audio Processing
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Data Compression Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
- Keywords
- predictive coding, speech coding, adaptive linear prediction, linear predictive coding, adaptive predictor, mean square error minimization, speech quality, bit rate reduction
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