Rahul Chitturi

Learn More
Speech is the most prominent and natural form of communication between humans. Human beings have long been motivated to create computer that can understand and talk like human. When the research tries to develop certain recognition system they require certain previously stored data i. e. database for respective recognition system. There are various speech(More)
In this paper, we discuss our efforts in the development of Indian language speech databases in Tamil, Telugu and Marathi for building large vocabulary speech recognition systems. We have collected speech data from about 560 speakers in these three languages. We discuss the design and methodology of collection of speech databases. We also present(More)
The variation in speech due to dialect is a factor which significantly impacts speech system performance. In this study, we investigate effective methods of combining acoustic and language information to take advantage of (i) speaker based acoustic traits as well as (ii) content based word selection across the text sequence. For acoustics, a GMM based(More)
The training of precise speech recognition models depends on accurate segmentation of the phonemes in a training corpus. Segmentation is typically performed using HMMs, but recent speech recognition work suggests that the transient acoustic features characteristic of manner-class phoneme boundaries (landmarks) may be more precisely localized using acoustic(More)
The training of precise speech recognition models depends on accurate segmentation of the phonemes in a training corpus. Segmentation is typically performed using HMMs, but recent speech recognition work suggests that the transient acoustic features characteristic of manner-class phoneme boundaries (landmarks) may be more precisely localized using acoustic(More)
Building an Automatic Speech Recognition System for a language requires a good amount of clean speech data and significant effort in training it. More so for foreign language speech recognition, where the native accent of the speaker brings about, a considerable difference in the pronunciation. In this paper, we propose a neural network based approach to(More)
  • 1