Use this interface to transcribe spoken Luxembourgish audio recordings into propperly written text adhering to the current spelling rules. Either upload an audio file (wav, mp3 or mp4) or use the microphone to record some audio. Hit Transcribe! After a certain time, the text will appear below. You can also try the examples.

Upload Audio File

Record from Microphone




Audio Language

Diarization

Output format

Word Timestamps

Translation

[with diarization and JSON]



 




Available options

Several audio input languages are avialable (default: Luxembourgish). If the recording contains more than one speaker, setting diarization to ‚On‘ will separate the text of every speaker in the recording along with time codes for their turns. Note that diarization adds some extra time to the recognition process. Three output formats are available: plain text (txt), SubRip Subtitles (srt), JSON (with or without time codes for words) and Praat TextGrid. These files can be downloaded through the link below the transcription. The recognition duration sums up to approximately 10 to 20% of the duration of the audio file. Once the recognition process has started, an estimated time and as well as a timer will be displayed to keep track of the progress. As an experimental feature translation to other languages has been added, which can output the recognized text in English, German, Portuguese or French. Note that these translations take more time to run and are only available for short audios (up to 2 minutes).

The maximal size for upload is 500 MB (for audio in wav format and a sampling frequency of 16000 Hz).

Note that the actual speech recognition recognition is run on a GPU server outside Europe. At any time of the recognition, we do not have access to the uploaded audio files. After completion of the recognition, all files will be deleted immediately. Do not upload recordings with sensitive data.

Contact

For more information about the setup and functioning of Lux-ASR, see here. Lux-ASR is under constant development by Peter Gilles, Léopold Hillah, and Nina Hosseini-Kivanani at the University of Luxembourg and is supported by the Chambre des Députes du Grand-Duché de Luxembourg. Contact us for more information.

References

Gilles, Peter, Nina Hosseini Kivanani & Léopold Edem Ayité Hillah. 2023. LUX-ASR: Building an ASR system for the Luxembourgish language. In 2022 IEEE Spoken Language Technology Workshop (SLT) SLT 2022, 1147–1149. Doha, Qatar. https://orbilu.uni.lu/handle/10993/55105.
Gilles, Peter, Nina Hosseini Kivanani & Léopold Edem Ayité Hillah. 2023. ASRLux: Automatic speech recognition for the low-resource language Luxembourgish. In International Conference of Phonetic Sciences (ICPhS), August 7-11, 2023, 3091–3095. Prague: Guarant International. https://hdl.handle.net/10993/55819.