Speech segmentation is an important sub problem of automatic speech recognition. This research is concerned with the development of a continuous speech segmentation system using Bangla Language. This paper presents a dynamic thresholding algorithm to segment the continuous Bngla speech sentences into words/sub-words. The research uses Otsu’s method for dynamic thresholding and introduces a new ...

Few studies have examined connected speech in demented and non-demented patients with Parkinson's disease (PD). We assessed the speech production of 35 patients with Lewy body spectrum disorder (LBSD), including non-demented PD patients, patients with PD dementia (PDD), and patients with dementia with Lewy bodies (DLB), in a semi-structured narrative speech sample in order to characterize impai...

This paper describes a hidden Markov model (HMM) based speech synthesis system developed for the Blizzard Challenge 2012. In the Blizzard Challenge 2012, we focused on a design of contexts for using audio books as training data and duration modeling of silence between sentences for synthesizing paragraphs. It is well known that contextual factors affect speech. We use extended contexts for usin...

A Swedish Hearing In Noise Test (HINT), consisting of everyday sentences to be used in an adaptive procedure to estimate the speech recognition thresholds in noise and quiet, has been developed. The material consists of 250 sentences, with a length of five to nine syllables, normalized for naturalness, difficulty and reliability. The sentences were recorded with a female speaker. From the sente...

ASR has long attracted attention for call center monitoring systems. In the ASR technology for call center conversations, the system usually divides an input signal into separate utterances and eliminates the unneeded silence parts of the signal before doing ASR processing on the detected utterances. This means the input signal should be split into utterances of the proper length for both ASR p...

This study tested the hypothesis that the previously reported advantage of musicians over non-musicians in understanding speech in noise arises from more efficient or robust coding of periodic voiced speech, particularly in fluctuating backgrounds. Speech intelligibility was measured in listeners with extensive musical training, and in those with very little musical training or experience, usin...