Spatio-Temporal Analysis of Spontaneous Speech with Microphone Arrays
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
This paper proposes a technique that segments into speaker turns based on their location, essentially implementing a discrete source tracking system. In many multi-party conversations, such as meetings or teleconferences, the location of participants is re ...
Audio segmentation, in general, is the task of segmenting a continuous audio stream in terms of acoustically homogenous regions, where the rule of homogeneity depends on the task. This thesis aims at developing and investigating efficient, robust and unsup ...
Microphone arrays are useful in meeting rooms, where speech needs to be acquired and segmented. For example, automatic speech segmentation allows enhanced browsing experience, and facilitates automatic analysis of large amounts of data. Spontaneous multi-p ...
This paper investigates the use of microphone arrays to acquire and recognise speech in meetings. Meetings pose several interesting problems for speech processing, as they consist of multiple competing speakers within a small space, typically around a tabl ...
Speaker turn detection is an important task for many speech processing applications. However, accurate segmentation can be hard to achieve if there are multiple concurrent speakers (overlap), as is typically the case in multi-party conversations. In such c ...
Microphone arrays are useful in meeting rooms, where speech needs to be acquired and segmented. For example, automatic speech segmentation allows enhanced browsing experience, and facilitates automatic analysis of large amounts of data. Spontaneous multi-p ...
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 ...
Speaker turn detection is an important task for many speech processing applications. However, accurate segmentation can be hard to achieve if there are multiple concurrent speakers (overlap), as is typically the case in multi-party conversations. In such c ...
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 ...
Tracking speakers in multiparty conversations constitutes a fundamental task for automatic meeting analysis. In this paper, we present a probabilistic approach to jointly track the location and speaking activity of multiple speakers in a multisensor meetin ...
