Open AccessPerformance Evaluation of Mel and Bark Scale based Features for Text-Independent Speaker Identification
Author(s) -
S. B. Dhonde,
Amol Chaudhari,
M. P. Gajare
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.k1999.0981119
Subject(s) - scale (ratio) , speech recognition , bark (sound) , identification (biology) , speaker recognition , computer science , filter bank , filter (signal processing) , pattern recognition (psychology) , artificial intelligence , biology , botany , geography , ecology , computer vision , cartography
The performance of Mel scale and Bark scale is evaluated for text-independent speaker identification system. Mel scale and Bark scale are designed according to human auditory system. The filter bank structure is defined using Mel and Bark scales for speech and speaker recognition systems to extract speaker specific speech features. In this work, performance of Mel scale and Bark scale is evaluated for text-independent speaker identification system. It is found that Bark scale centre frequencies are more effective than Mel scale centre frequencies in case of Indian dialect speaker databases. Mel scale is defined as per interpretation of pitch by human ear and Bark scale is based on critical band selectivity at which loudness becomes significantly different. The recognition rate achieved using Bark scale filter bank is 96% for AISSMSIOIT database and 95% for Marathi database.