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State-of-the-art acoustic models for Automatic Speech Recognition (ASR) are based on Hidden Markov Models (HMM) and Deep Neural Networks (DNN) and often require thousands of hours of transcribed speech data during training. Therefore, building multilingual ...
In this paper, we develop Automatic Speech Recognition (ASR) systems for multi-genre speech recognition of low-resource languages where training data is predominantly conversational speech but test data can be in one of the following genres: news broadcast ...
We experiment with subword segmentation approaches that are widely used to address the open vocabulary problem in the context of end-to-end automatic speech recognition (ASR). For morphologically rich languages such as German which has many rare words main ...
A new software for modeling pathological speech signals is presented in this paper. The software is called NeuroSpeech. This software enables the analysis of pathological speech signals considering different speech dimensions: phonation, articulation, pros ...
What are the pressing questions in architecture – in teaching, research and practice? Based on their many years of experience, professors Inès Lamunière and Laurent Stalder come together in five meetings to search for answers. They describe an approach to ...
Open-domain chatbots that can engage in a conversation on any topic received significant attention in the last several years, which opened opportunities for studying user interaction with them. Drawing from reviews of chatbots posted on Google Play, we exp ...
Idiap has made a submission to the conversational telephony speech (CTS) challenge of the NIST SRE 2019. The submission consists of six speaker verification (SV) systems: four extended TDNN (E-TDNN) and two TDNN x-vector systems. Employment of various trai ...
We build a conversational agent which knowledge base is an online forum for parents of autistic children. We collect about 35,000 threads totalling some 600,000 replies, and label 1% of them for usefulness using Amazon Mechanical Turk. We train a Random Fo ...
State-of-the-art automatic speech recognition (ASR) and text-to-speech systems require a pronunciation lexicon that maps each word to a sequence of phones. Manual development of lexicons is costly as it needs linguistic knowledge and human expertise. To fa ...
We describe the design and recording of a high quality French speech corpus, aimed at building TTS systems, investigate multiple styles, and emphasis. The data was recorded by a French voice talent, and contains about ten hours of speech, including emphasi ...