In the wide domain of automatic speech recognition, extracting the relevant information carried by the speech signal is far from easy. Diversity, redundancy, and variability, the main characteristics of the speech signal, make this task particularly difficult. The work reported here presents a multi
Gender Gates for Telephone-Based Automatic Speaker Recognition
β Scribed by Pierre Castellano; Stefan Slomka; Peter Barger
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 331 KB
- Volume
- 7
- Category
- Article
- ISSN
- 1051-2004
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β¦ Synopsis
The present work demonstrates a need for enhancing text-independent, telephone based, automatic speaker recognition systems with a gender gate. A range of gender gates and speech parameter types are proposed for this problem. These gates and parameters are also investigated in the context of speech degraded by coding and reverberation. It is found that the performance of the most accurate gender gates and speech parameters is similar for uncoded, coded, and reverberated speech. However, the most accurate gender gates and speech parameter types differ slightly across the three scenarios. The most robust all-round gender gates consist of two Mahalanobis distance classifiers with fused outputs or pitch fused to the output of one such classifier. The best all-round speech parameters were reflection and Mel-based cepstrum coefficients.
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