Searched for: contributor%3A%22Scharenborg%2C+O.E.+%28mentor%29%22
(1 - 19 of 19)
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Dekker, Bo (author)To enable communication for patients who have lost the ability to speak due to severe neuromuscular diseases, covert speech based brain-computer interfaces (BCIs) might be used. These system use neural signals arising from covert speech and translate them into text or synthesised speech. Covert speech is imagining to speak without moving any of...master thesis 2022
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Zhang, Yixuan (author)One of the most important problems that needs tackling for wide deployment of Automatic Speech Recognition (ASR) is the bias in ASR, i.e., ASRs tend to generate more accurate predictions for certain speaker groups while making more errors on speech from others. In this thesis, we aim to reduce bias against non-native speakers of Dutch compared...master thesis 2022
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Ji, Hang (author)In this thesis, we analyzed and compared speech representations extracted from different frozen self-supervised learning (SSL) speech pre-trained models on their ability to capture articulatory feature (AF) information and their subsequent prediction of phone recognition performance in within-language and cross-language scenarios. Specifically,...master thesis 2022
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Sweijen, Neal (author)ASR (automatic speech recognition) systems are used widely in our current day and age. However, for a technology that is used so much in our daily life it contains a lot of bias. This means that not all people can use it equally, people with a different gender, age and dialect will all see different results. The goal of this paper is to reduce...bachelor thesis 2022
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Marinov, Alves (author)A problem prevalent in many modern-day Automatic Speech Recognition (ASR) systems is the presence of bias and its reduction. Bias can be observed when an ASR system performs worse on a subset of its speakers compared to the rest rather than having the same overall generalization for everyone. This can be seen by using Word Error Rates (WER) as a...bachelor thesis 2022
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Zhlebinkov, Nikolay (author)Automatic speech recognition (ASR) does not perform equally well on every speaker. There is bias against many attributes, including accent. To train Dutch ASR, there exists CGN(Corpus Gesproken Nederlands) and as an extension, the JASMIN corpus with annotated accented data. This paper focuses on improving ASR performance for NRAD (Northern...bachelor thesis 2022
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Mešić, Amar (author)Building Automatic Speech Recognizers (ASRs) has been a challenge in languages with insufficiently sized corpora or data sets. A further large issue in language corpora is biases against regionally accented speech and other speaker attributes. There are some techniques to improve ASR performance and reduce biases in these corpora, known as data...bachelor thesis 2022
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Bălan, Dragos (author)There are many experiments conducted with Automatic Speech Recognition (ASR) systems, but many either focus on specific speaker categories or on a language in general. Therefore, bias could occur in such ASR systems towards different genders, age groups, or dialects. But, to analyze and reduce bias, the models require significant amounts of data...bachelor thesis 2022
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Zhang, Yuanyuan (author)Automatic Speech Recognition (ASR) systems have seen substantial improvements in the past decade; however, not for all speaker groups. Recent research shows that bias exists against different types of speech, including non-native accents, in state-of-the-art (SOTA) ASR systems. To attain inclusive speech recognition, i.e., ASR for everyone...master thesis 2022
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- Gao, Lingyun (author) master thesis 2021
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- Prananta, Luke (author) master thesis 2021
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Chiroşca, Mihail (author)A limitation of current ASR systems is the so-called out-of-vocabulary words. The solution to overcome this limitation is to use APR systems. Previous research on Dutch APR systems identified Time Delayed Bidirectional Long-Short Term Memory Neural Network (TDNN-BLSTM) as one of best performing state-of-the-art NN architecture for PR. The goal...bachelor thesis 2021
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van der Tang, Jordy (author)This research expands past research on implementing the TDNN-OPGRU network for Automatic Phoneme Recognition on Dutch speech by implementing and testing the TDNN-OPGRU network on Mandarin speech. The goal of this research is to investigate the performance of the TDNN-OPGRU architecture when decoding phonemes in Mandarin prepared and spontaneous...bachelor thesis 2021
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Klom, Irene (author)This research studies the Projected Bidirectional Long Short-Term Memory Time Delayed Neural Network (TDNN-BLSTM) model for English phoneme recognition. It contributes to the field of phoneme recognition by analyzing the performance of the TDNN-BLSTM model based on the TIMIT corpus and the Buckeye corpus, respectively containing read speech and...bachelor thesis 2021
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Levenbach, Robert (author)In this research, Dutch phoneme recognition (PR) is researched and improved. The last research on Dutch PR dates back to 1995. This research presents Dutch PR in modern daylight by researching state-of-the-art techniques found in research on other languages and implementing them on Dutch PR. The goal of this research is to find the current best...master thesis 2021
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van der Hout, J.R.T.E. (author)Image2Speech is the relatively new task of generating a spoken description of an image. Similar to Automatic Image Captioning, it is a task focused on describing images, however it avoids the usage of textual resources. An Image2Speech system produces a sequences of phonemes instead of (written) words which makes the Image2Speech task applicable...master thesis 2020
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Tian, Tian (author)Visually grounded speech representation learning has shown to be useful in the field of speech representation learning. Studies of learning visually grounded speech embedding adopted speech-image cross-modal retrieval task to evaluate the models, since the cross-modal retrieval task allows to jointly learn both modalities and find their...master thesis 2020
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Scholten, J.S.M. (author)A Visually Grounded Speech model is a neural model which is trained to embed image caption pairs closely together in a common embedding space. As a result, such a model can retrieve semantically related images given a speech caption and vice versa. The purpose of this research is to investigate whether and how a Visually Grounded Speech model...master thesis 2020
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Chandi, Mitchel (author)Sound pollution is a common concern in urban environments. Many cities are therefore equipped with networks of microphones, which are merely used to identify loud areas and less loud areas. Additional information, other than the sound levels, is not derived. It is unknown which sound events are responsible for the recorded sound levels. This...master thesis 2020
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