Name
Title | ||
|---|---|---|
4800 Bps RELP Vocoder using vector quantization for both filter and residual representations |
Abstract | ||
|---|---|---|
The paper presents the full description and discusses the performances of a 4800 bit per second residual excited linear prediction vocoder. The LPC analysis is efficiently performed using a type of binary-tree search vector-quantization approach. The technique, which is described in ref (1), uses a set of hyperplane equations to perform a hierarchical pattern classification of the input autocorrelation vector in the autocorrelation space. The end result of the search is the integer i1which is the index of the most appropriate (in the Itakura-distance sense) prediction filter out of a set of N preset filters. The search requires only dot products. In this case vector quantization presents two advantages over the classical approach of the Durbin algorithm followed by scalar quantization. First, a faster algorithm is obtained. Second, the same accuracy in filter representation is possible with less bits per second and consequently more bits can be allocated for representing the residual and gain. The residual is vector quantized in the time domain by blocks of 16 the samples according to the approach of ref (2). The 16 sample block is essentially encoded using the integer I2which is the index of the most appropriate 16-sample waveform out of set of M preset prototype waveforms stored in memory. The paper includes preference testings for comparison with other types of 4800 Kbit/sec vocoders. Some sample recordings will be presented at the conference. Finally, preliminary results in the attempt to implement the vocoder in real time on a MAP 200 array processor are discussed. |
Year | DOI | Venue |
|---|---|---|
1982 | 10.1109/ICASSP.1982.1171774 | Acoustics, Speech, and Signal Processing, IEEE International Conference ICASSP '82. |
Keywords | Field | DocType |
autocorrelation,binary tree,vector quantization,real time,testing,prototypes,linear predictive coding,time domain | Computer science,Vector quantization,Artificial intelligence,Hyperplane,Dot product,Linear predictive coding,Autocorrelation,Time domain,Residual,Pattern recognition,Algorithm,Speech recognition,Vector processor | Conference |
Volume | Citations | PageRank |
7 | 1 | 0.49 |
References | Authors | |
2 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. Adoul | 1 | 290 | 63.42 |
| Philippe Mabilleau | 2 | 1 | 0.49 |