Title :
Automatic Speech Recognition of accented Hindi data
Author :
Kumari, Prapti ; Shakina Deiv, D. ; Bhattacharya, Mahua
Author_Institution :
Comput. Sci. & Eng. Dept., ABV-Indian Inst. Inf. Technol. & Manage., Gwalior, India
Abstract :
Inter-speaker variability resulting from factors such as gender, emotions, accent and age lead to the decrease in recognition accuracy of speaker-independent Automatic Speech Recognition systems. Accent variation in Hindi speech and its effect on the performance of Continuous Speech Hindi ASR was studied with the objective to design and develop a compensation technique for accent variation. This paper presents the results of the preliminary experiments conducted in the process.
Keywords :
natural language processing; speech recognition; Hindi speech; accent variation; accented Hindi data; compensation technique; continuous speech Hindi ASR; inter-speaker variability; speaker-independent automatic speech recognition systems; Adaptation models; Computational modeling; Digital divide; Feature extraction; Hidden Markov models; Training; Transforms; Accent variation; Automatic Speech Recognition; Recognition Accuracy; accent modeling;
Conference_Titel :
Computation of Power, Energy, Information and Communication (ICCPEIC), 2014 International Conference on
Conference_Location :
Chennai
Print_ISBN :
978-1-4799-3826-1
DOI :
10.1109/ICCPEIC.2014.6915342
