Phoneme Probability Presentation of Continuous Speech based on Phoneme Spotting
نویسنده
چکیده
SUMMARY This paper describes a new presentation of continuous speech in terms of the probability of all phoneme types as a function of time. The presentation is called a phoneme probability presentation (PPP) and can be used for phoneme recognition of continuous speech. As a technique ,,0 produce the PPP, we have employed hidden Markov models (HMM) with time duration information. This information is essential to spot the phonemes and to produce the PPP. With this information the HMMs of all the phoneme types can compute their probability in parallel and in time synchronism. The PPP can serve as phoneme filters which can produce phoneme probability from continuous speech.
منابع مشابه
Comparison of keyword spotting approaches for informal continuous speech
This paper describes several approaches to keyword spotting (KWS) for informal continuous speech. We compare acoustic keyword spotting, spotting in word lattices generated by large vocabulary continuous speech recognition and a hybrid approach making use of phoneme lattices generated by a phoneme recognizer. The systems are compared on carefully defined test data extracted from ICSI meeting dat...
متن کاملPhoneme Based Acoustics Keyword Spotting in Informal Continuous Speech
This paper describes several ways of keywords spotting (KWS), based on Gaussian mixture (GM) hidden Markov modelling (HMM). Context-independent and dependent phoneme models are used in our system. The system was trained and evaluated on informal continuous speech. We used different complexities of KWS recognition networks and different types of phoneme models. The impact of these parameters on ...
متن کاملImproving 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...
متن کاملبهبود عملکرد سیستم بازشناسی گفتار پیوسته بوسیله ویژگیهای استخراج شده از مانیفولدهای گفتاری در فضای بازسازی شده فاز
The design for new feature extraction methods out of the speech signal and combination of their obtained information is one of the most effective approaches to improve the performance of automatic speech recognition (ASR) system. Recent researches have been shown that the speech signal contains nonlinear and chaotic properties, but the effects of these properties are not used in the continuous ...
متن کاملSpotting Japanese CV-Syllables and Phonemes Using Time-Delay Neural Networks
Syllable or phoneme spotting if reliably achieved, provides a good solution to the spoken word andlor continuous speech recognition problem, . We previously showed tha t the Time-Delay Neural Network (TDNN) provided excellent recognition performance (98.6%) of the "BDG" consonant task. We would also like to extend the encouraging performance of TDNN to wordlcontinuous speech recognition. In thi...
متن کامل