Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 70 for “"automatic speech recognition (ASR)"”.
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Incorporating pitch features for tone modeling in automatic recognition of Mandarin Chinese
… of pitch data should improve the performance of automatic speech recognition (ASR) systems on Mandarin Chinese. The focus of this thesis is to improve the performance of a non-tonal automatic speech recognition (ASR) system on a Mandarin Chinese corpus by implementing modifications to the system …
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Improving searchability of automatically transcribed lectures through dynamic language modelling
… can enable faster navigation and searching. Automatic speech recognition (ASR) technologies may be used to create automated transcripts, to avoid the significant time and cost involved in manual transcription.
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Improving performance of a GSM-based speech recognizer
… if we could get the machines to understand human speech, we could be able to communicate with people (and even make communicating with computers open to many people). This is the main motivation behind Automatic Speech Recognition (ASR) as a field of research, to enable machines to recognize human …
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Visual Speech Recognition Using a 3D Convolutional Neural Network
<p>Main stream automatic speech recognition (ASR) makes use of audio data to identify spoken words, however visual speech recognition (VSR) has recently been of increased interest to researchers. VSR is used when audio data is corrupted or missing entirely and also to further enhance the accuracy …
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Lip Detection and Adaptive Tracking
<p>Performance of automatic speech recognition (ASR) systems utilizing only acoustic information degrades significantly in noisy environments such as a car cabins. Incorporating audio and visual information together can improve performance in these situations. This work proposes a lip detection and …
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Evaluation of the usability and usefulness of automatic speech recognition among users in South Africa
An automatic speech recognition (ASR) system is a software application which recognizes human speech, processes it as input, and displays a text version of the speech as output or uses the input as commands for another application's usage. ASR can either be speaker-dependent or speaker-independent. …
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Toward More Intelligible Simultaneous Multi-channel Speech Enhancement and Recognition
<p>Traditional single-channel speech enhancement and separation methods focus on enhancing the target speech signal by suppressing the noise and interfering speech signal. The methods suffer from nonlinear distortion brought by the algorithm, which hurts the intelligibility of the speech and also …
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Self-Supervised Audio-Visual Speech Diarization and Recognition
Many real world use cases of automatic speech recognition (ASR) contain video and multiple speakers, such as TV broadcasts and video conferences. However, state-of-the-art end-to-end multimodal ASR models generally do not support diarization. This thesis extends one such model, AV-HuBERT, to …
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TASK- AND DOMAIN-DEPENDENT NATURAL LANGUAGE PROCESSING FOR SUPPORTING SPOKEN DOCUMENT USE
… prototypes. The presented field studies identify Automatic Speech Recognition (ASR) and Sentiment Analysis (SA) as two requisite NLP technologies for supporting information seekers in the studied domain. The dissertation also demonstrates how SA models can be optimized with TDD feedback taken into …
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Analyzing Icelandic conversation using State-of-the-Art ASR models
… performance and fine-tuning of transformer-based Automatic Speech Recognition (ASR) systems applied to Icelandic conversational speech, with a primary focus on OpenAI’s Whisper model and a secondary fo- cus on Meta’s Wav2Vec 2.0. The study uses the Spjallrómur dataset, a 21-hour unscripted …
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Towards an end-to-end music transcription system using neural networks
… It has notable parallels with the task of Automatic Speech Recognition (ASR) and indeed from this connection arises some natural Machine Learning-based approaches. However, these methods usually involve carefully designed preprocessing steps, or transcription into less flexible …
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Adaptation of hybrid deep neural network-hidden Markov model speech recognition system using a sub-space approach
The performance of automatic speech recognition (ASR) system can be enhanced by adaptation of the ASR for a particular speaker or a group of speakers. In ASR, training and testing data often do not follow the same statistics; they are often mismatched, which leads to a gap in performance. The …
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Effective automatic speech recognition data collection for under–resourced languages
As building transcribed speech corpora for under-resourced languages plays a pivotal role in developing automatic speech recognition (ASR) technologies for such languages, a key step in developing these technologies is the effective collection of ASR data, consisting of transcribed audio and …
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Machine learning and deep learning techniques for natural language processing with application to audio recordings
… of the recordings to text was done using Automatic Speech Recognition (ASR), followed by data cleaning and the transcribed text was represented in numerical form using the Term Frequency-Inverse Document Frequency (TF- IDF) and the Count Vectorizer. The study then compared the accuracy of …
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Robust Unconstrained Face Detection and Lip Localization Using Gabor Filters
Automatic speech recognition (ASR) is a well-researched field of study aimed at augmenting the man-machine interface through interpretation of the spoken word. From in-car voice recognition systems to automated telephone directories, automatic speech recognition technology is becoming increasingly …
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Parts-based models and local features for automatic speech recognition
While automatic speech recognition (ASR) systems have steadily improved and are now in widespread use, their accuracy continues to lag behind human performance, particularly in adverse conditions. This thesis revisits the basic acoustic modeling assumptions common to most ASR systems and argues …
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Language Modeling from Visually Grounded Speech
… language processing have significantly reduced automatic speech recognition (ASR) error rates, driven by large-scale supervised training on paired speech–text data and, more recently, self-supervised pre-training on unpaired speech and audio. These methods have facilitated robust transfer …
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Evaluating the Effects of Automatic Speech Recognition Word Accuracy
Automatic Speech Recognition (ASR) research has been primarily focused towards large-scale systems and industry, while other areas that require attention are often over-looked by researchers. For this reason, this research looked at automatic speech recognition at the consumer level. Many …
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Techniques for robust source separation and localization in adverse environments: Issues and performance of a new framework of emerging techniques for frequency-domain convolutive blind/semi-blind separation and localization of acoustic sources
… this problem is of high interest in the automatic speech recognition (ASR) community since it would improve the effectiveness of a natural human-machine interaction. Among numerous methods of multichannel blind source separation techniques, those based on the Independent Component …
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Implementing a distributed approach for speech resource and system development
The range of applications for high-quality automatic speech recognition (ASR) systems has grown dramatically with the advent of smart phones, in which speech recognition can greatly enhance the user experience. Currently, the languages with extensive ASR support on these devices are languages that …
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