Text-informed audio source separation. Example-based approach using non-negative matrix partial co-factorizationReportar como inadecuado




Text-informed audio source separation. Example-based approach using non-negative matrix partial co-factorization - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

1 PANAMA - Parcimonie et Nouveaux Algorithmes pour le Signal et la Modélisation Audio Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE 2 Technicolor R & I Cesson Sévigné

Abstract : The so-called informed audio source separation, where the separation process is guided by some auxiliary information, has recently attracted a lot of research interest since classical blind or non-informed approaches often do not lead to satisfactory performances in many practical applications. In this paper we present a novel text-informed framework in which a target speech source can be separated from the background in the mixture using the corresponding textual information. First, given the text, we propose to produce a speech example via either a speech synthesizer or a human. We then use this example to guide source separation and, for that purpose, we introduce a new variant of the non-negative matrix partial co-factorization NMPCF model based on a so-called excitation-filter-channel speech model. Such a modeling allows sharing the linguistic information between the speech example and the speech in the mixture. The corresponding multiplicative update MU rules are eventually derived for the parameters estimation and several extensions of the model are proposed and investigated. We perform extensive experiments to assess the effectiveness of the proposed approach in terms of source separation and alignment performance.





Autor: Luc Le Magoarou - Alexey Ozerov - Ngoc Duong -

Fuente: https://hal.archives-ouvertes.fr/



DESCARGAR PDF




Documentos relacionados