An enhanced relative spectral processing of speech

• 来源期刊: 声学学报（英文版）
• 学科: 工学
• 年，卷（期）: 2002,（1）
• 页码范围: 86-96
• 页数: 11页
• 分类号: TB5
• 语种: 英文

摘要

An enhanced relative spectral (E_RASTA) technique for speech and speaker recognition is proposed. The new method consists of classical RASTA filtering in logarithmic spectral domain following by another additive RASTA filtering in the same domain. In this manner,both the channel distortion and additive noise are removed effectively. In speaker identification and speech recognition experiments on TI46 database, the E_RASTA performs equal or better than J_RASTA method in both tasks. The E_RASTA does not need the speech SNR estimation in order to determinate the optimal value of J in J_RASTA, and the information of how the speech degrades. The choice of E_RASTA filter also indicates that the low temporal modulation components in speech can deteriorate the performance of both recognition tasks. Besides, the speaker recognition needs less temporal modulation frequency band than that of the speech recognition.