R
Raghava Krishnan
Researcher at Indian Institute of Technology Madras
Publications - 5
Citations - 145
Raghava Krishnan is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Speech synthesis & Syllable. The author has an hindex of 4, co-authored 5 publications receiving 126 citations.
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A common attribute based unified HTS framework for speech synthesis in Indian languages.
B. Ramani,S. Lilly Christina,Rachel G. Anushiya,V. Sherlin Solomi,Mahesh Kumar Nandwana,Anusha Prakash,S. Aswin Shanmugam,Raghava Krishnan,S. Kishore Prahalad,K. Samudravijaya,P. Vijayalakshmi,T. Nagarajan,Hema A. Murthy +12 more
TL;DR: The common phoneset and common question set are used to build HTS based systems for six Indian languages, namely, Hindi, Marathi, Bengali, Tamil, Telugu and Malayalam, and a uniform HMM framework for building speech synthesisers is proposed.
Proceedings ArticleDOI
A syllable-based framework for unit selection synthesis in 13 Indian languages
Hemant A. Patil,Tanvina B. Patel,Nirmesh J. Shah,Hardik B. Sailor,Raghava Krishnan,G. R. Kasthuri,T. Nagarajan,Lilly Christina,Naresh Kumar,Veera Raghavendra,Surekha Kishore,S. R. M. Prasanna,Nagaraj Adiga,Sanasam Ranbir Singh,Konjengbam Anand,Pranaw Kumar,Bira Chandra Singh,S. L. Binil Kumar,T. G. Bhadran,T. Sajini,Arup Saha,T. K. Basu,K. Sreenivasa Rao,N. P. Narendra,Anil Kumar Sao,Rajesh Kumar,Pranhari Talukdar,Purnendu Acharyaa,Somnath Chandra,Swaran Lata,Hema A. Murthy +30 more
TL;DR: A consortium effort on building text to speech (TTS) systems for 13 Indian languages using the same common framework and the TTS systems are evaluated using Mean Opinion Score (DMOS) and Word Error Rate (WER).
Proceedings ArticleDOI
Building speech synthesis systems for Indian languages
Abhijit Pradhan,Anusha Prakash,S. Aswin Shanmugam,G. R. Kasthuri,Raghava Krishnan,Hema A. Murthy +5 more
TL;DR: New efforts to build text-to-speech synthesis systems (TTS) for Indian languages is presented and a group delay based syllable segmentation semi-automatic tool is discussed, showing that automatic segmentation is preferred.
Indian Language Screen Readers and Syllable Based Festival Text-to-Speech Synthesis System
Anila Susan Kurian,Badri Narayan,Nagarajan Madasamy,Ashwin Bellur,Raghava Krishnan,Kasthuri G,Vinodh M. Vishwanath,Kishore Prahallad,Hema A. Murthy +8 more
TL;DR: The development and evaluation of syllable-based Indian language Text-To-Speech (TTS) synthesis system (around festival TTS) with ORCA and NVDA, for Linux and Windows environments respectively.
Tonic-Independent Stroke Transcription of the Mridangam
TL;DR: This paper obtains feature vectors that encode tonic-invariance by computing the magnitude spectrum of the constant-Q transform of the audio signal, and uses Non-negative Matrix Factorization (NMF) to obtain a low-dimensional feature space where mridangam strokes are separable.