Just‐Noticeable Differences for Phoneme Duration in Natural Speech

Additional use of phoneme duration hypotheses in automatic speech segmentation

In this paper, we describe a new approach for speaker independent automatic phoneme alignment. Typical algorithms for this task use only phoneme-to-frame similarity measures which are somehow maximised or minimised. In addition to such similarity measures, we use phoneme duration hypotheses generated by the speech synthesis system HADIFIX [1]. For algorithms based on dynamic programming, it is ...

Improving Phoneme Sequence Recognition using Phoneme Duration Information in DNN-HSMM

Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There are two phases in DNN-based phoneme recognition systems including training and testing. Mos...

Phoneme-level speech and natural language intergration for agglutinative languages

A new tightly coupled speech and natural language integration model is presented for a TDNN-based large vocabulary continuous speech recognition system. Unlike the popular n-best techniques developed for integrating mainly HMM-based speech and natural language systems in word level, which is obviously inadequate for the morphologically complex agglutinative languages, our model constructs a spo...

Phoneme resistance during speech-in-speech comprehension

This study investigates masking effects occurring during speech comprehension in the presence of concurrent speech signals. We examined the differential effects of 4to 8-talker babble (natural speech) or babble-like noise (reversed speech) on word identification. We measured phoneme identification rates. Results showed that different types of linguistic information can interfere with speech rec...

Perceptual Differences in Natural Speech and Personalized Synthetic Speech