Consonantal Cues for Automatic Speech Recognition

A Database for Automatic Persian Speech Emotion Recognition: Collection, Processing and Evaluation

Abstract   Recent developments in robotics automation have motivated researchers to improve the efficiency of interactive systems by making a natural man-machine interaction. Since speech is the most popular method of communication, recognizing human emotions from speech signal becomes a challenging research topic known as Speech Emotion Recognition (SER). In this study, we propose a Persian em...

Predicting Automatic Speech Recognition Performance Using Prosodic Cues

In spoken dialogue systems, it is important for a system to know how likely a speech recognition hypothesis is to be correct, so it can reprompt for fresh input, or, in cases where many errors have occurred, change its interaction strategy or switch the caller to a human attendant. We have discovered prosodic features which more accurately predict when a recognition hypothesis contains a word e...

Automatic speech recognition for children

In this paper, the acoustic and linguistic characteristics of children speech are investigated in the context of automatic speech recognition. Acoustic variability is identi ed as a major hurdle in building high performance ASR applications for children. A simple speaker normalization algorithm combining frequency warping and spectral shaping introduced in [5] is shown to reduce acoustic variab...

Automatic speech recognition

Automatic Term Recognition using Contextual Cues

In this paper we present an approach for the extraction of multi-word terms from special language corpora. the new element is the incorporation of context information for the evaluation of candidate terms. This information is embedded to the C-value method in the form of statistical weights.