Innovative technologies for under-resourced language documentation: The BULB Project

International audienceThe project Breaking the Unwritten Language Barrier (BULB), which brings together linguists and computer scientists, aims at supporting linguists in documenting unwritten languages. In order to achieve this we will develop tools tailored to the needs of documentary linguists by building upon technology and expertise from the area of natural language processing, most prominently automatic speech recognition and machine translation. As a development and test bed for this we have chosen three less-resourced African languages from the Bantu family: Basaa, Myene and Embosi. Work within the project is divided into three main steps: 1) Collection of a large corpus of speech (100h per language) at a reasonable cost. After initial recording, the data is re-spoken by a reference speaker to enhance the signal quality and orally translated into French. 2) Automatic transcription of the Bantu languages at phoneme level and the French translation at word level. The recognized Bantu phonemes and French words will then be automatically aligned. 3) Tool development. In close cooperation and discussion with the linguists, the speech and language technologists will design and implement tools that will support the linguists in their work, taking into account the linguists' needs and technology's capabilities. The data collection has begun for the three languages. For this we use standard mobile devices and a dedicated software—LIG-AIKUMA, which proposes a range of different speech collection modes (recording, respeaking, translation and elicitation). LIG-AIKUMA 's improved features include a smart generation and handling of speaker metadata as well as respeaking and parallel audio data mapping

Innovative technologies for under-resourced language documentation: The BULB Project

International audienceThe project Breaking the Unwritten Language Barrier (BULB), which brings together linguists and computer scientists, aims at supporting linguists in documenting unwritten languages. In order to achieve this we will develop tools tailored to the needs of documentary linguists by building upon technology and expertise from the area of natural language processing, most prominently automatic speech recognition and machine translation. As a development and test bed for this we have chosen three less-resourced African languages from the Bantu family: Basaa, Myene and Embosi. Work within the project is divided into three main steps: 1) Collection of a large corpus of speech (100h per language) at a reasonable cost. After initial recording, the data is re-spoken by a reference speaker to enhance the signal quality and orally translated into French. 2) Automatic transcription of the Bantu languages at phoneme level and the French translation at word level. The recognized Bantu phonemes and French words will then be automatically aligned. 3) Tool development. In close cooperation and discussion with the linguists, the speech and language technologists will design and implement tools that will support the linguists in their work, taking into account the linguists' needs and technology's capabilities. The data collection has begun for the three languages. For this we use standard mobile devices and a dedicated software—LIG-AIKUMA, which proposes a range of different speech collection modes (recording, respeaking, translation and elicitation). LIG-AIKUMA 's improved features include a smart generation and handling of speaker metadata as well as respeaking and parallel audio data mapping

Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the “Speaking rosetta” JSALT 2017 workshop

International audienceWe summarize the accomplishments of a multidisciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and words) in a language without orthography. We study the replacement of orthographic transcriptions by images and/or translated text in a well-resourced language to help unsuper-vised discovery from raw speech

Human Translations Guided Language Discovery for ASR Systems

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Linguistic unit discovery from multi-modal inputs in unwritten languages: Summary of the “Speaking rosetta” JSALT 2017 workshop

International audienceWe summarize the accomplishments of a multidisciplinary workshop exploring the computational and scientific issues surrounding the discovery of linguistic units (subwords and words) in a language without orthography. We study the replacement of orthographic transcriptions by images and/or translated text in a well-resourced language to help unsuper-vised discovery from raw speech

Speech technology for unwritten languages

International audienceSpeech technology plays an important role in our everyday life. Speech is, among others, used for human-computer interaction, including, for instance, information retrieval and on-line shopping. In the case of an unwritten language, however, speech technology is unfortunately difficult to create, because it cannot be created by the standard combination of pre-trained speech-to-text and text-to-speech subsystems. The research presented in this paper takes the first steps towards speech technology for unwritten languages. Specifically, the aim of this work was 1) to learn speech-to-meaning representations without using text as an intermediate representation, and 2) to test the sufficiency of the learned representations to regenerate speech or translated text, or to retrieve images that depict the meaning of an utterance in an unwritten language. The results suggest that building systems that go directly from speech-to-meaning and from meaning-to-speech, bypassing the need for text, is possible

Innovative technologies for under-resourced language documentation: The BULB Project

International audienceThe project Breaking the Unwritten Language Barrier (BULB), which brings together linguists and computer scientists, aims at supporting linguists in documenting unwritten languages. In order to achieve this we will develop tools tailored to the needs of documentary linguists by building upon technology and expertise from the area of natural language processing, most prominently automatic speech recognition and machine translation. As a development and test bed for this we have chosen three less-resourced African languages from the Bantu family: Basaa, Myene and Embosi. Work within the project is divided into three main steps: 1) Collection of a large corpus of speech (100h per language) at a reasonable cost. After initial recording, the data is re-spoken by a reference speaker to enhance the signal quality and orally translated into French. 2) Automatic transcription of the Bantu languages at phoneme level and the French translation at word level. The recognized Bantu phonemes and French words will then be automatically aligned. 3) Tool development. In close cooperation and discussion with the linguists, the speech and language technologists will design and implement tools that will support the linguists in their work, taking into account the linguists' needs and technology's capabilities. The data collection has begun for the three languages. For this we use standard mobile devices and a dedicated software—LIG-AIKUMA, which proposes a range of different speech collection modes (recording, respeaking, translation and elicitation). LIG-AIKUMA 's improved features include a smart generation and handling of speaker metadata as well as respeaking and parallel audio data mapping

FINDINGS OF THE IWSLT 2020 EVALUATION CAMPAIGN

The evaluation campaign of the International Conference on Spoken Language Translation (IWSLT 2020) featured this year six challenge tracks: (i) Simultaneous speech translation, (ii) Video speech translation, (iii) Offline speech translation, (iv) Conversational speech translation, (v) Open domain translation, and (vi) Non-native speech translation. A total of 30 teams participated in at least one of the tracks. This paper introduces each track's goal, data and evaluation metrics, and reports the results of the received submissions

FINDINGS OF THE IWSLT 2022 EVALUATION CAMPAIGN

The evaluation campaign of the 19th International Conference on Spoken Language Translation featured eight shared tasks: (i) Simultaneous speech translation, (ii) Offline speech translation, (iii) Speech to speech translation, (iv) Low-resource speech translation, (v) Multilingual speech translation, (vi) Dialect speech translation, (vii) Formality control for speech translation, (viii) Isometric speech translation. A total of 27 teams participated in at least one of the shared tasks. This paper details, for each shared task, the purpose of the task, the data that were released, the evaluation metrics that were applied, the submissions that were received and the results that were achieved