A 3-D Audio-Visual Corpus of Affective Communication
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
State-of-the-art automatic speech recognition (ASR) techniques are typically based on hidden Markov models (HMMs) for the modeling of temporal sequences of feature vectors extracted from the speech signal. At the level of each HMM state, Gaussian mixture m ...
State-of-the-art automatic speech recognition (ASR) techniques are typically based on hidden Markov models (HMMs) for the modeling of temporal sequences of feature vectors extracted from the speech signal. At the level of each HMM state, Gaussian mixture m ...
In the context of cognitive and behavioural therapies, the use of immersion technologies to replace classical exposure often improves the therapeutic process. As it is necessary to validate the efficiency of such a technique, both therapists and VR special ...
Accurate detection and segmentation of spontaneous multi-party speech is crucial for a variety of applications, including speech acquisition and recognition, as well as higher-level event recognition. However, the highly sporadic nature of spontaneous spee ...
State-of-the-art automatic speech recognition (ASR) techniques are typically based on hidden Markov models (HMMs) for the modeling of temporal sequences of feature vectors extracted from the speech signal. At the level of each HMM state, Gaussian mixture m ...
In human perception, the availability of context enhances recognition and renders it more robust to noise. Even if not all phonemes in a word (or words in a sentence etc.) are correctly perceived, humans can fill in missing parts with the help of cues from ...
In human perception, the availability of context enhances recognition and renders it more robust to noise. Even if not all phonemes in a word (or words in a sentence etc.) are correctly perceived, humans can fill in missing parts with the help of cues from ...
This work presents categorization experiments performed over noisy texts. By noisy it is meant any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g. transcriptions of speech recordings extracted with ...
The purpose of this paper is to investigate the behavior of HMM2 models for the recognition of noisy speech. It has previously been shown that HMM2 is able to model dynamically important structural information inherent in the speech signal, often correspon ...
Spoken Document Retrieval (SDR) consists in retrieving segments of a speech database that are relevant to a query. The state-of-the-art approach to the SDR problem consists in transcribing the speech data into digital text before applying common Informatio ...
