Speech coding is the application of data compression of digital audio signals containing speech. Speech coding uses speech-specific parameter estimation using audio signal processing techniques to model the speech signal, combined with generic data compression algorithms to represent the resulting modeled parameters in a compact bitstream.
The two most important applications of speech coding are mobile telephony and Voice over IP.
The techniques used in speech coding are similar to that in audio data compression and audio coding where knowledge in psychoacoustics is used to transmit only data that is relevant to the human auditory system. For example, in narrowband speech coding, only information in the frequency band 400 Hz to 3500 Hz is transmitted but the reconstructed signal is still adequate for intelligibility.
Speech coding differs from other forms of audio coding in that speech is a much simpler signal than most other audio signals, and that there is a lot more statistical information available about the properties of speech. As a result, some auditory information which is relevant in audio coding can be unnecessary in the speech coding context. In speech coding, the most important criterion is preservation of intelligibility and "pleasantness" of speech, with a constrained amount of transmitted data.
It should be emphasised that the intelligibility of speech includes, besides the actual literal content, also speaker identity, emotions, intonation, timbre etc. that are all important for perfect intelligibility. The more abstract concept of pleasantness of degraded speech is a different property than intelligibility, since it is possible that degraded speech is completely intelligible, but subjectively annoying to the listener.
In addition, most speech applications require low coding delay, as long coding delays interfere with speech interaction.
Sample companding viewed as a form of speech coding
From this viewpoint, the A-law and μ-law algorithms (G.711) used in traditional PCM digital telephony can be seen as a very early precursor of speech encoding, requiring only 8 bits per sample but giving effectively 12 bits of resolution. Although this would generate unacceptable distortion in a music signal, the peaky nature of speech waveforms, combined with the simple frequency structure of speech as a periodic waveform with a single fundamental frequency with occasional added noise bursts, make these very simple instantaneous compression algorithms acceptable for speech.
A wide variety of other algorithms were tried at the time, mostly variants on delta modulation, but after careful consideration, the A-law/μ-law algorithms were chosen by the designers of the early digital telephony systems. At the time of their design, their 33% bandwidth reduction for a very low complexity made them an excellent engineering compromise. Their audio performance remains acceptable, and there has been no need to replace them in the stationary phone network.
In 2008, G.711.1 codec, which has a scalable structure, was standardized by ITU-T. The input sampling rate is 16 kHz.
Modern speech compression
Much of the later work in speech compression was motivated by military research into digital communications for secure military radios, where very low data rates were required to allow effective operation in a hostile radio environment. At the same time, far more processing power was available, in the form of VLSI integrated circuits, than was available for earlier compression techniques. As a result, modern speech compression algorithms could use far more complex techniques than were available in the 1960s to achieve far higher compression ratios.
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