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Showing 1 to 20 of 448 for “"speech recognition"”.

  1. Speech Recognition under Stress

    … Southern Illinois University- Carbondale. TITLE: SPEECH RECOGNITION UNDER STRESS MAJOR PROFESSOR: Dr. Nazeih M. Botros In this dissertation, three techniques, Dynamic Time Warping (DTW), Hidden Markov Models (HMM), and Hidden Control Neural Network (HCNN) are utilized to realize talker-independent …

    siu-theses Repository record for Speech Recognition under Stress (opens in a new tab)

  2. Speech recognition of foreign accent

    This thesis investigates the application of AutoRegressive (AR) modeling techniques on single syllable words to detect foreign accents in spoken American English. The study involves thirty-one native American English speakers, and six native Brazilian speakers. Five different distance measures are …

    nps Repository record for Speech recognition of foreign accent (opens in a new tab)

  3. On-device mobile speech recognition

    Despite many years of research, Speech Recognition remains an active area of research in Artificial Intelligence. Currently, the most common commercial application of this technology on mobile devices uses a wireless client – server approach to meet the computational and memory demands of the …

    nott-trent Repository record for On-device mobile speech recognition (opens in a new tab)

  4. Automatic Speech Recognition Quality Estimation

    Evaluation of automatic speech recognition (ASR) systems is difficult and costly, since it requires manual transcriptions. This evaluation is usually done by computing word error rate (WER) that is the most popular metric in ASR community. Such computation is doable only if the manual references …

    trento Repository record for Automatic Speech Recognition Quality Estimation (opens in a new tab)

  5. Speech recognition in adverse environments

    east-anglia

  6. Speech recognition in programmable logic

    Speech recognition is a computationally demanding task, especially the decoding part, which converts pre-processed speech data into words or sub-word units, and which incorporates Viterbi decoding and Gaussian distribution calculations. In this thesis, this part of the recognition process is …

    birmingham Repository record for Speech recognition in programmable logic (opens in a new tab)

  7. Improving multilingual speech recognition systems

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-04-06 without embargo terms

    uiuc Repository record for Improving multilingual speech recognition systems (opens in a new tab)

  8. Spontaneous speech recognition using HMMs

    This thesis describes a speech recognition system that was built to support spontaneous speech understanding. The system is composed of (1) a front end acoustic analyzer which computes Mel-frequency cepstral coefficients, (2) acoustic models of context-dependent phonemes (triphones), (3) a back-off …

    mit Repository record for Spontaneous speech recognition using HMMs (opens in a new tab)

  9. Energy-scalable speech recognition circuits

    … with speaking to machines, the applications of speech interfaces will diversify and include a wider range of devices, such as wearables, appliances, and robots. Automatic speech recognition (ASR) is a key component of these interfaces that is computationally intensive. This thesis shows how we …

    mit Repository record for Energy-scalable speech recognition circuits (opens in a new tab)

  10. Fractal based speech recognition and synthesis

    … message is most often the primary purpose of speech com­munication and the recognition of this message by machine that would be most useful. This research consists of two major parts. The first part presents a novel and promis­ing approach for estimating the degree of recognition of speech

    de-montfort Repository record for Fractal based speech recognition and synthesis (opens in a new tab)

  11. Multiview feature learning for speech recognition

    … transformation of acoustic feature vectors for speech recognition, in a framework where apart from the acoustics, additional views are available at training time. We consider a multiview learning approach based on canonical correlation analysis to learn linear transformations of the acoustic …

    uiuc Repository record for Multiview feature learning for speech recognition (opens in a new tab)

  12. Consonant landmark detection for speech recognition

    … of abrupt acoustic discontinuities in the speech signal, which constitute landmarks for consonant sounds. Because a large amount of phonetic information is concentrated near acoustic discontinuities, more focused speech analysis and recognition can be performed based on the landmarks. Three …

    mit Repository record for Consonant landmark detection for speech recognition (opens in a new tab)

  13. Pronunciation learning for automatic speech recognition

    … remains the Achilles heel of modern automatic speech recognizers (ASRs). Unlike stochastic acoustic and language models that learn the values of their parameters from training data, the baseform pronunciations of words in an ASR vocabulary are typically specified manually, and do not change, …

    mit Repository record for Pronunciation learning for automatic speech recognition (opens in a new tab)

  14. Subword lexical modelling for speech recognition

    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.

    mit Repository record for Subword lexical modelling for speech recognition (opens in a new tab)

  15. Multimodal speech recognition with ultrasonic sensors

    … of articulator movement is an area of multimodal speech recognition that has not been researched extensively. The widely-researched audio-visual speech recognition (AVSR), which relies upon video data, is awkwardly high-maintenance in its setup and data collection process, as well as …

    mit Repository record for Multimodal speech recognition with ultrasonic sensors (opens in a new tab)

  16. Speaker model adaptation in automatic speech recognition.

    One of the main obstacles of automatic speech recognition is to achieve speaker independence. It is generally believed that the main difficulty is the inter-speaker variability in which the acoustic characteristics of different speakers are not the same. There are mainly three approaches to …

    rgu Repository record for Speaker model adaptation in automatic speech recognition. (opens in a new tab)

  17. Hidden Markov model based visual speech recognition

    Speech recognition can be made more accurate if visual speech information such as the movement of the lips is taken into consideration. In this thesis, studies on visual speech processing are presented. Classifiers based on Hidden Markov Model (HMM) are first explored for modeling and identifying …

    nus Repository record for Hidden Markov model based visual speech recognition (opens in a new tab)

  18. Speech recognition by computer: algorithms and architectures

    … of algorithms and architectures for computer recognition of human speech. Three speech recognition algorithms have been implemented, using (a) Walsh Analysis, (b) Fourier Analysis and (c) Linear Predictive Coding. The Fourier Analysis algorithm made use of the Prime-number Fourier Transform …

    greenwich

  19. Pronunciation modeling for large vocabulary speech recognition

    … variability of words in conversational speech is one of the major causes of low accuracy in automatic speech recognition (ASR). Many pronunciation modeling approaches have been developed to address this problem. Some explicitly manipulate the pronunciation dictionary as well as the set …

    uiuc Repository record for Pronunciation modeling for large vocabulary speech recognition (opens in a new tab)

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