Speaker Adaptation is a technique which is used to improve the recognition accuracy of Automatic Speech Recognition (ASR) systems. Here, we report a study of the impact of online speaker adaptation on the performance of a speaker independent, continuous speech recognition system for Hindi language. The speaker adaptation is performed using the Maximum Likelihood Linear Regression (MLLR) transfo...

The transformation of vocal characteristics aims at modifying voice such that the intelligibility of aphonic voice is increased or the voice characteristics of a speaker (source speaker) to be perceived as if another speaker (target speaker) had uttered it. In this paper, the current state-of-the-art voice characteristics transformation methodology is reviewed. Special emphasis is placed on voi...

In this paper, we apply Constrained Maximum a Posteriori Linear Regression (CMAPLR) transformation on Universal Background Model (UBM) when characterizing each speaker with a supervector. We incorporate the covariance transformation parameters into the supervector in addition to the mean transformation parameters. Maximum Likelihood Linear Regression (MLLR) covariance transformation is adopted....

Voice transformation is the process of using a small amount of speech data from a target speaker to build a transformation model that can be used to generate arbitrary speech that sounds like the target speaker. One common current technique is building Gausian Mixture Models to map spectral aspects from source to target speakers. This paper proposes the use of duration models to improve the tra...

We present a multi-speaker formant synthesizer based on parameter concatenation. The user can choose among three speakers, two males and one female. The synthesizer stores all the parameters for the basic speaker and linear transformation functions to synthesized the other two. The complete database for one speaker consists of 455 parameterized units (diphones, triphones,...) and the parameters...

Voice conversion consists in transforming a source speaker voice into a target speaker voice. There are many applications of voice conversion systems where the amount of training data from the source speaker and the target speaker is different. Usually, the amount of source data available is large, but it is desired to estimate the transformation with a small amount of target data. Systems base...

This paper presents a new scheme for developing a voice conversion system that modiies the utterance of a source speaker to sound like speech from a target speaker. We refer to the method as Speaker Transformation Algorithm using Segmen-tal Codebooks (STASC). Two new methods are described to perform the transformation of vocal tract and glottal excita-tion characteristics across speakers. In ad...

This paper describes a similar speaker selection technique based on distance metric learning. Our aim is selection of a perceptually similar speaker using acoustic features from a multispeaker database. A novel point of the proposed technique is training a transform matrix using the perceptual voice quality similarity between many speakers obtained from a subjective evaluation to convert acoust...

In this paper we explore the importance of speaker specific information carried in the glottal source. We time align utterances of two speakers speaking the same sentence from the TIMIT database of American English. We then extract the glottal flow derivative from each speaker and interchange them. Through time alignment and this glottal flow transformation, we can make a speaker of a northern ...