--- language: "en" thumbnail: tags: - Spoken language understanding license: "CC0" datasets: - Timers and Such metrics: - Accuracy --- # End-to-end SLU model for Timers and Such Attention-based RNN sequence-to-sequence model for [Timers and Such](https://arxiv.org/abs/2104.01604) trained on the `train-real` subset. This model checkpoint achieves 86.7% accuracy on `test-real`. The model uses an ASR model trained on LibriSpeech ([`speechbrain/asr-crdnn-rnnlm-librispeech`](https://huggingface.co/speechbrain/asr-crdnn-rnnlm-librispeech)) to extract features from the input audio, then maps these features to an intent and slot labels using a beam search. The dataset has four intents: `SetTimer`, `SetAlarm`, `SimpleMath`, and `UnitConversion`. Try testing the model by saying something like "set a timer for 5 minutes" or "what's 32 degrees Celsius in Fahrenheit?" You can try the model on the `math.wav` file included here as follows: ``` from speechbrain.pretrained import EndToEndSLU slu = EndToEndSLU.from_hparams("speechbrain/slu-timers-and-such-direct-librispeech-asr") slu.decode_file("speechbrain/slu-timers-and-such-direct-librispeech-asr/math.wav") ``` #### Referencing SpeechBrain ``` @misc{SB2021, author = {Ravanelli, Mirco and Parcollet, Titouan and Rouhe, Aku and Plantinga, Peter and Rastorgueva, Elena and Lugosch, Loren and Dawalatabad, Nauman and Ju-Chieh, Chou and Heba, Abdel and Grondin, Francois and Aris, William and Liao, Chien-Feng and Cornell, Samuele and Yeh, Sung-Lin and Na, Hwidong and Gao, Yan and Fu, Szu-Wei and Subakan, Cem and De Mori, Renato and Bengio, Yoshua }, title = {SpeechBrain}, year = {2021}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\\\\\\\\url{https://github.com/speechbrain/speechbrain}}, } ``` #### Referencing Timers and Such ``` @misc{lugosch2021timers, title={Timers and Such: A Practical Benchmark for Spoken Language Understanding with Numbers}, author={Lugosch, Loren and Papreja, Piyush and Ravanelli, Mirco and Heba, Abdelwahab and Parcollet, Titouan}, year={2021}, eprint={2104.01604}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```