In this study, we propose a maximum a posterior (MAP) estimation of channel bias to compensate the channel mismatch in telephone speech recognition. For a telephone speech, the channel bias is estimated by maximizing a posterior probability. Because a posterior probability is composed of a likelihood function and a prior density, we introduce a scale factor to evaluate their weights in MAP estimation. To further improve the performance, a prior channel statistics is extended to multiple components and the channel mismatch is separately compensated for different segments. Besides, a rapid MAP estimation applied in feature domain is also proposed for reducing the computational complexity. Experiments show that proposed method can significantly improve recognition ares and computational complexity.
|Number of pages||4|
|State||Published - 1 Dec 1996|
|Event||Proceedings of the 1996 International Conference on Spoken Language Processing, ICSLP. Part 1 (of 4) - Philadelphia, PA, USA|
Duration: 3 Oct 1996 → 6 Oct 1996
|Conference||Proceedings of the 1996 International Conference on Spoken Language Processing, ICSLP. Part 1 (of 4)|
|City||Philadelphia, PA, USA|
|Period||3/10/96 → 6/10/96|