Search Results for "speech analysis"

Source code from the Research Institute for Signals, Systems and Computational Intelligence http://fich.unl.edu.ar/sinc

RDRPOSTagger is a robust, easy-to-use and language-independent rule-based toolkit for Part-of-Speech (POS) and morphological tagging. RDRPOSTagger obtains fast performance in both learning and tagging process. RDRPOSTagger also achieves a very competitive accuracy in comparison to the state-of-the-art results. RDRPOSTagger now supports pre-trained POS and morphological tagging models for Bulgarian, Czech, Dutch, English, French, German, Hindi, Italian, Portuguese, Spanish, Swedish, Thai...

The project supports the Welsh Language Technology domain with a set of NLP tools that drive innovation and advance the development of sophisticated textual analysis solutions. The WNLT project delivers four core NLP modules; a) Word Segmentation for separating text into words b) Sentence Boundary Disambiguation for finding sentence boundaries c) Part of Speech Tagger for determining the part of speech of each word d) Morphological Analyser for identifying the root form (lemma) of words. ...

Yet Another Audio Feature Extractor is a toolbox for audio analysis. Easy to use and efficient at extracting a large number of audio features simultaneously. WAV and MP3 files supported, or embedding in C++, Python or Matlab applications.

AraMorph is an Arabic morphological analyzer and part-of-speech tagger.

JTextPro: A Java-based Text Processing tool that includes sentence boundary detection (using maximum entropy classifier), word tokenization (following Penn conventions), part-of-speech tagging (using CRFTagger), and phrase chunking (using CRFChunker).

The Text Annotation Environment (tae) can be used to annotate natural language text manually or automatically (UIMA Annotator) with meta information (tokens, part-of-speech, named entities, ...). Tae is based on Eclipse and IBM's UIMA.

CRFTagger: Conditional Random Fields Part-of-Speech (POS) Tagger for English. The model was trained on sections 01..24 of WSJ corpus and using section 00 as the development test set (accuracy of 97.00%). Tagging speed: 500 sentences/s.

Italian labeled digits corpus, good for speech recognition. Corpus di cifre italiane segmentato, adatto a esperimenti di riconoscimento vocale e riconoscimento fonetico.

AutoSummary uses Natural Language Processing to generate a contextually-relevant synopsis of plain text. It uses statistical and rule-based methods for part-of-speech tagging, word sense disambiguation, sentence deconstruction and semantic analysis.

jATLAS is a Java implementation of ATLAS [Architecture and Tools for Linguistic Analysis Systems]. For more information, see http://jatlas.sourceforge.net.

This is a project to create a compiler that converts grammars written in SRGS standard (http://www.w3.org/TR/speech-grammar/) to a graph understandable by HMM based ASR engines. Check srgs-parser.sf.net