Improved Language Identification in Presence of Speech Coding
| Autor: | Anil Kumar Vuppala, Ravi Kumar Vuddagiri, Jiteesh Varma Bhupathiraju, Suryakanth V. Gangashetty, Hari Krishna Vydana |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Voice activity detection
Language identification Sonorant Computer science Speech recognition Speech coding Speech technology Speech corpus 02 engineering and technology Speech processing 030507 speech-language pathology & audiology 03 medical and health sciences Sonority hierarchy 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing 0305 other medical science |
| Zdroj: | Mining Intelligence and Knowledge Exploration ISBN: 9783319268316 MIKE |
| Popis: | Automatically identifying the language being spoken from speech plays a vital role in operating multilingual speech processing applications. A rapid growth in the use of mobile communication devices has inflicted the necessity of operating all speech processing applications in mobile environments. Degradation in the performance of any speech processing applications is majorly due to varying background environments, speech coding and transmission errors. In this work, we focus on developing a language identification system robust to degradations in coding environments in Indian scenario. Spectral features MFCC extracted from high sonority regions of speech are used for language identification. Sonorant regions of speech are the regions of speech that are perceptually loud, carry a clear pitch. The quality of coded speech in high sonority region is high compared to less sonorant regions. Spectral features MFCC extracted from high sonority regions of speech are used for language identification. In this work, GMM-UBM based modelling technique is employed to develop an language identification LID system. Present study is carried out on IITKGP-MLILSC speech database. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|