Essays about: "Automatic language identification"
Showing result 1 - 5 of 16 essays containing the words Automatic language identification.
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1. Identification and Classification of TTS Intelligibility Errors Using ASR : A Method for Automatic Evaluation of Speech Intelligibility
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In recent years, applications using synthesized speech have become more numerous and publicly available. As the area grows, so does the need for delivering high-quality, intelligible speech, and subsequently the need for effective methods of assessing the intelligibility of synthesized speech. READ MORE
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2. Context-aware Swedish Lexical Simplification : Using pre-trained language models to propose contextually fitting synonyms
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : This thesis presents the development and evaluation of context-aware Lexical Simplification (LS) systems for the Swedish language. In total three versions of LS models, LäsBERT, LäsBERT-baseline, and LäsGPT, were created and evaluated on a newly constructed Swedish LS evaluation dataset. READ MORE
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3. Exploring Automatic Synonym Generation for Lexical Simplification of Swedish Electronic Health Records
University essay from Linköpings universitet/Institutionen för hälsa, medicin och vårdAbstract : Electronic health records (EHRs) are used in Sweden's healthcare systems to store patients' medical information. Patients in Sweden have the right to access and read their health records. Unfortunately, the language used in EHRs is very complex and presents a challenge for readers who lack medical knowledge. READ MORE
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4. Application of formal verification and validation on modern multi-functional signalling system
University essay from KTH/TransportplaneringAbstract : Demand for rail transport is increasing day by day. Rail is popular in public transport due to punctuality, regularity, and safety. However, we hear daily that rail traffic still has many problems to solve about incidents, near misses, and signal errors. READ MORE
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5. Construction of a machine learning training pipeline for merging AIS data with external datasources
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : Machine learning methods are increasingly being used in the maritime domain to predict traffic anomalies and to mitigate risk, for example avoiding collision and groundingaccidents. However, most machine learning systems used for detecting such issues hasbeen trained predominately on single data sources such as vessel positioning data. READ MORE