A speech recognition system implements the task of automatically transcribing speech into text. As computer power has advanced and sophisticated tools have become available, there has been significant progress in this field. But a huge gap still exists between the performance of the Automatic Speech Recognition (ASR) systems and human listeners. In this thesis, a novel signal analysis technique...

In this paper we present a short survey of automatic speech recognition systems underlining the current achievements and capabilities of current day solutions as well as their inherent limitations and shortcomings. In response to which we propose an improved paradigm and algorithm for building an automatic speech recognition system that actively adapts its recognition model in an unsupervised f...

This study was aimed to evaluate the relative contributions of spectral and temporal information to Korean phoneme recognition and to compare them with those to English phoneme recognition. Eleven normal-hearing Korean-speaking listeners participated in the study. Korean phonemes, including 18 consonants in a /Ca/ format and 17 vowels in a /hVd/ format, were processed through a noise vocoder. T...

This work assesses different approaches for speech and non-speech segmentation of audio data and proposes a new, high-level representation of audio signals based on phoneme recognition features suitable for speech/non-speech discrimination tasks. Unlike previous model-based approaches, where speech and non-speech classes were usually modeled by several models, we develop a representation where ...

Out-of-vocabulary (OOV) words are the most challenging problem in automatic speech recognition (ASR), especially for morphologically rich languages. Most end-to-end systems performed at word and character levels of a language. Amharic is poorly resourced but This paper proposes hybrid connectionist temporal classification with attention architecture syllabification algorithm system (AASR) using...

M efficient rejection method is implemented for the HMM based small vocabulary isolated word recognition system. Six clustered phoneme models are generated using statistical method from the 45 context independent Korean phoneme models which were trained using the phonetically balanced Korean speech database and the classification through likelihood ratio scoring is performed based on the cluste...

Environmental sounds are very helpful in understanding environmental situations and in telling the approach of danger, and sound-imitation words (sound-related onomatopoeia) are important expressions to inform such sounds in human communication, especially in Japanese language. In this paper, we design a method to recognize sound-imitation words (SIWs) for environmental sounds. Critical issues ...

In this paper we tackle the task of bootstrapping an Automatic Speech Recognition system without an a priori given language model, a pronunciation dictionary, or transcribed speech data for the target language Slovene – only untranscribed speech and translations to other resource-rich source languages of what was said are available. Therefore, our approach is highly relevant for under-resourced...

We describe a new method for phoneme sequence recognition given a speech utterance, which is not based on the HMM. In contrast to HMM-based approaches, our method uses a discriminative kernel-based training procedure in which the learning process is tailored to the goal of minimizing the Levenshtein distance between the predicted phoneme sequence and the correct sequence. The phoneme sequence p...