Proposed Speech Coder Research Articles

A MFCC-Based CELP Speech Coder for Server-Based Speech Recognition in Network Environments

Existing standard speech coders can provide high quality speech communication. However, they tend to degrade the performance of automatic speech recognition (ASR) systems that use the reconstructed speech. The main cause of the degradation is in that the linear predictive coefficients (LPCs), which are typical spectral envelope parameters in speech coding, are optimized to speech quality rather than to the performance of speech recognition. In this paper, we propose a speech coder using mel-frequency cepstral coefficients (MFCCs) instead of LPCs to improve the performance of a server-based speech recognition system in network environments. To develop the proposed speech coder with a low-bit rate, we first explore the interframe correlation of MFCCs, which results in the predictive quantization of MFCC. Second, a safety-net scheme is proposed to make the MFCC-based speech coder robust to channel errors. As a result, we propose an 8.7 kbps MFCC-based CELP coder. It is shown that the proposed speech coder has a comparable speech quality to 8 kbps G.729 and the ASR system using the proposed speech coder gives the relative word error rate reduction by 6.8% as compared to the ASR system using G.729 on a large vocabulary task (AURORA4).

Robust speaker verification in low bit rate channels

The coder mismatch problem in speaker verification systems is addressed. A speech coder detector is proposed that correctly classifies the coding scheme used in a given utterance having a length of 3 s with an average rate of 93%. It is shown that, with the use of the proposed speech coder detector, the average speaker verification accuracy over a pool of four different coders used in low bit rate communication channels is increased close to the average accuracy obtained in the ideal matched case.

A very low bit rate speech coder based on a recognition/synthesis paradigm

Previous studies have shown that a concatenative speech synthesis system with a large database produces more natural sounding speech. We apply this paradigm to the design of improved very low bit rate speech coders (sub 1000 b/s). The proposed speech coder consists of unit selection, prosody coding, prosody modification and waveform concatenation. The encoder selects the best unit sequence from a large database and compresses the prosody information. The transmitted parameters include unit indices and the prosody information. To increase naturalness as well as intelligibility, two costs are considered in the unit selection process: an acoustic target cost and a concatenation cost. A rate-distortion-based piecewise linear approximation is proposed to compress the pitch contour. The decoder concatenates the set of units, and then synthesizes the resultant sequence of speech frames using the harmonic+noise model (HNM) scheme. Before concatenating units, prosody modification which includes pitch shifting and gain modification is applied to match those of the input speech. With single speaker stimuli, a comparison category rating (CCR) test shows that the performance of the proposed coder is close to that of the 2400-b/s MELP coder at an average bit rate of about 800-b/s during talk spurts.