With this interface, it is possible to convert Luxembourgish audio recordings into written text. 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

Audio Language


Output format

Word Timestamps


[with diarization and JSON]

Additional options

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 we have added translation,which can output the recognized text in English, German, Portuguese or French. Note that these translations take more time to run.

The maximal size for upload is 500 MB (for wav, 16000 Hz sampling frequency). Note that the 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.


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.


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.