Download the Technology Catalog in pdf here.
Download the Technology Catalog in pdf here.
Question-answering is for both the general public to retrieve precise
information in raw texts, and for companies and organizations, that have
specific text mining needs. Question-answering systems suggest short answers and their justification passage to questions provided in natural language.
Extension of search engine, technology monitoring
The targeted users and customers of language recognition technologies
are actors in the multimedia and call center sectors, including academic
and industrial organizations, as well as actors in the defense domain,
interested in the processing of audio documents, and in particular if
the collection of documents contains multiple languages.
A language identification system can be run prior to a speech recognizer. Its output is used to load the appropriate language dependent speech recognition models for the audio document.
Alternatively, the language identification might be used to dispatch
audio documents or telephone calls to a human operators fluent in the
corresponding identified language.
Other potential applications also involve the use of LID as a front-end to a multi-lingual translation system. This technology can also be part of automatic system for spoken data retrieval or automatic enriched transcriptions.
End-user application, Question-Answering is the easiest way to find information for everybody: ask the question as you want and obtain answers, not snippets or pages.
Search and find precise answers in any collection of texts, from the Web
or any other source (voice recognition, optical character recognition,
etc.), with eventual correction of the source text, ability to generate
questions from generic requests, eventually a single word, ability to
find similar questions and their answers, etc.
Monolingual and multilingual Question-Answering system. Languages: English, French (+ Spanish, Portuguese, Polish, with partners using the same API).
The targeted users and customers are the multimedia industry actors, and
all academic or industrial laboratories interested in object tracking
Automatic music summary generation aims at providing informative audio preview of the content of a music file (rather than the commonly used first 30s). It can therefore benefit to any service providing access to music items requiring a quick preview of the music files such as music providers, online music portals. It can also be installed on a personal computer as a preview of the local user’s music collection.
Automatic music structure estimation provides the description of the temporal organization of music files in terms of repetition of parts over time. It can be used for visualization and interaction with the playing of a music file (intelligent forward/ backward, accessing directly the most repeated parts). It can benefit to any developer of music players or software for music interaction.
Classification of music items are generally primarily based on their belonging to a music genre: electronica, jazz, pop/ rock… However, the editorial meta-data related
to the genre are generally only accessible at the artist level (the
whole set of music tracks produced by one artist will belong to the same
music genre whatever the tracks content). Ircammusicgenre is a software which allows the automatic estimation of the belonging of a music track to music genres. The list of music genres considered by the software can be
pre-determined by Ircam (electronica, jazz, pop/rock…) or can be adapted
to categories relevant to the partner, provided a sufficient number of
sound examples per category.
Ircammusicgenre also allows to perform multi-labeling of a music track,
i.e. assigning a set of genre labels instead of a single genre. In this case, a weighting is assigned to each estimated label.
Ircammusicmood a software which allows the automatic estimate of the music mood of has music track to music mood. Music mood report to the “mood” that a track suggests: positive, sad, powerful, calming…
As for the music genre, the list can be predetermined by Ircam or discussed with the partner. Multi-labels can also be applied to the music mood classification.
Web Question-answering is an end-user application. FIDJI is an open-domain QA system for French and English
Information retrieval on the Web or in document collections
Everyone who has to deal with electronic document encoding of from the
original source material and needs to consider the hierarchical
structure represented in the digitized document.
Everyone who has to deal with document image analysis.
Layout analysis is the first major step in a document image analysis workflow. The correctness of the output of page segmentation and region
classification is crucial as the resulting representation is the basis
for all subsequent analysis and recognition processes.
Domain-speciﬁc communities, especially technical and scientiﬁc, willing
to build search engines and information systems to manage documents with
ﬁne-grained semantic annotations.
Search engines and information systems development.