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• Samrómur-Children Demonstration Scripts 22.01

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  The "Samrómur-Children Demonstration Scripts 22.01" is a set of three code recipes intended to show how to integrate the corpus "Samrómur Children's Icelandic Speech Data 21.09" and the "Icelandic Language Models with Pronunciations 22.01" to create automatic speech recognition systems using the Kaldi toolkit. „Samrómur-Sýnisforskriftir fyrir börn 22.01“ er safn af þremur talgreiningarforskriftum sem sýna hvernig má beita talmálheildinni „Samrómur-Íslensk talgögn frá börnum 21.09“ ásamt „Íslenskum mállíkönum með framburðarorðabók 22.01“ til þess að byggja talgreiningarkerfi með verkfærakistunni Kaldi.

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• Face-domain-specific automatic speech recognition models

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  This entry contains all the files required to implement face-domain-specific automatic speech recognition (ASR) applications using the Kaldi ASR toolkit (https://github.com/kaldi-asr/kaldi), including the acoustic model, language model, and other relevant files. It also includes all the scripts and configuration files needed to use these models for implementing face-domain-specific automatic speech recognition. The acoustic model was trained using the relevant Kaldi ASR tools (https://github.com/kaldi-asr/kaldi) and the Artur speech corpus (http://hdl.handle.net/11356/1776; http://hdl.handle.net/11356/1772). The language model was trained using the domain-specific text data involving face descriptions obtained by translating the Face2Text English dataset (https://github.com/mtanti/face2text-dataset) into the Slovenian language. These models, combined with other necessary files like the HCLG.fst and decoding scripts, enable the implementation of face-domain-specific ASR applications. Two speech corpora ("test" and "obrazi") and two Kaldi ASR models ("graph_splosni" and "graph_obrazi") can be selected for conducting speech recognition tests by setting the variable "graph" and "test_sets" in the "local/test_recognition.sh" script. Acoustic speech features can be extracted and speech recognition tests can be conducted using the "local/test_recognition.sh" script. Speech recognition test results can be obtained using the "results.sh" script. The KALDI_ROOT environment variable also needs to be set in the script "path.sh" to set the path to the Kaldi ASR toolkit installation folder.

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• Heyra (1.0)

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  Heyra is an Android application that provides three loosely coupled components, an implementation of Android's speech recognition interface, an intent handler activity for speech recognition actions from other applications and an input method service (i.e. virtual keyboard) that can either be used on its own or launched by supported applications. Heyra can be downloaded from the Google Play Store at https://play.google.com/store/apps/details?id=is.tiro.heyra Heyra er Android forrit sem inniheldur þrjá laustengda hluta; útfærslu á kerfisþjónustu í Android fyrir talgreiningu, meðhöndlara fyrir talgreiningaraðgerðir frá öðrum forritum og inntaksþjónustu (eða sýndarlyklaborð) sem hægt er að nota eitt og sér eða kalla á úr öðrum studdum forritum. Hægt er að sækja Heyra á Google Play Store á https://play.google.com/store/apps/details?id=is.tiro.heyra

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