Adaptation Experiments on French MediaParl ASR

This document summarizes adaptation experiments done on French MediaParl corpus and other French corpora. Baseline adaptation techniques are briefly presented and evaluated in the MediaParl task for speaker adaptation, speaker adaptive training, database combination and environmental adaptation. Results show that by applying baseline adaptation techniques, a relative WER reduction of up to 22.8% can be reached in French transcription accuracy. For the MediaParl task, performance of systems trained on directly merged databases and of systems trained on databases combined via MAP adaptation did not differ significantly when large amount of data was available. During the experiments, French data recorded in Switzerland behaved in a similar way compared to French data recorded in France, which suggest that French spoken in Valais is close to the standard French spoken in France, and differencies in ASR accuracies between models trained on Swiss MediaParl and on French BREF are more likely caused by environmental factors or more spontaneity in speech

Using Phonological Phrase Segmentation to Improve Automatic Keyword Spotting for the Highly Agglutinating Hungarian Language

This paper investigates the usage of prosody for the improvement of keyword spotting, focusing on the highly agglutinating Hungarian language, where keyword spotting cannot be effectively performed using LVCSR, as such systems are either unavailable or hard to operate due to high OOV rates and poor N-gram language modelling capabilities. Therefore, the applied keyword spotting system is based on confidence scores computed as a ratio of acoustic scores obtained in two ways: firstly, by decoding with an universal background model; and secondly, by decoding with a keyword model embedded into filler models. Prosody is used to perform an automatic phonological phrase alignment for speech, proven to be useful for automatic partial word boundary detection in fixed stress languages. Several features deduced from the phonological phrase alignment are investigated to rescore baseline confidence scores both in a rule-based and in a data-driven manner. Results show that in relevant operating points of the system, a false alarm reduction of 10% - 40% can be reached by the same miss probability rates

Automatic Speech Indexing System of Bilingual Video Parliament Interventions

This paper presents the development and evaluation of an automatic audio indexing system designed for a special task: work in a bilingual environment in the Parliament of the Canton of Valais in Switzerland, with two official languages, German and French. As several speakers are bilingual, language changes may occur within speaker or even within utterance. Two audio indexing approaches are presented and compared: in the first, speech indexing is based on bilingual automatic speech recognition; in the second, language identification is used after speaker diarization in order to select the corresponding monolingual speech recognizer for decoding. The approaches are later combined. Speaker adaptive training is also addressed and evaluated. Accuracy of language identification and speech recognition for the monolingual and bilingual cases are presented and compared, in parallel with a brief description of the system and the user interface. Finally, the audio indexing system is also evaluated from an information retrieval point of view

The SP2 SCOPES Project on Speech Prosody

This is an overview of a Joint Research Project within the Scientific co-operation between Eastern Europe and Switzerland (SCOPES) Program of the Swiss National Science Foundation (SNFS) and Swiss Agency for Development and Cooperation (SDC). Within the SP2 SCOPES Project on Speech Prosody, in the course of the following two years, the four partners aim to collaborate on the subject of speech prosody and advance the extraction, processing, modeling and transfer of prosody for a large portfolio of European languages: French, German, Italian, English, Hungarian, Serbian, Croatian, Bosnian, Montenegrin, and Macedonian. Through the intertwined four research plans, synergies are foreseen to emerge that will build a foundation for submitting strong joint proposals for EU funding

Design of a Speech Corpus for Research on Cross-Lingual Prosody Transfer

Since the prosody of a spoken utterance carries information about its discourse function, salience, and speaker attitude, prosody mod- els and prosody generation modules have played a crucial part in text-to- speech (TTS) synthesis systems from the beginning, especially those set not only on sounding natural, but also on showing emotion or particular speaker intention. Prosody transfer within speech-to-speech translation is a recent research area with increasing importance, with one of its most important research topics being the detection and treatment of salient events, i.e. instances of prominence or focus which do not result from syn- tactic constraints, but are rather products of semantic or pragmatic level eects. This paper presents the design and the guidelines for the creation of a multilingual speech corpus containing prosodically rich sentences, ultimately aimed at training statistical prosody models for multilingual prosody transfer in the context of expressive speech synthesis