diff --git a/nemo/collections/asr/data/audio_to_audio.py b/nemo/collections/asr/data/audio_to_audio.py index a3c6dd0cc1b3..9f9eda7c865a 100644 --- a/nemo/collections/asr/data/audio_to_audio.py +++ b/nemo/collections/asr/data/audio_to_audio.py @@ -636,7 +636,7 @@ def get_duration(audio_files: List[str]) -> List[float]: Returns: List of durations in seconds. """ - duration = [librosa.get_duration(path=f) for f in flatten(audio_files)] + duration = [librosa.get_duration(filename=f) for f in flatten(audio_files)] return duration def load_embedding(self, example: collections.Audio.OUTPUT_TYPE) -> Dict[str, torch.Tensor]: diff --git a/nemo/collections/asr/models/enhancement_models.py b/nemo/collections/asr/models/enhancement_models.py index 7cc5c3d8459f..5dad4f58f3d2 100644 --- a/nemo/collections/asr/models/enhancement_models.py +++ b/nemo/collections/asr/models/enhancement_models.py @@ -135,7 +135,7 @@ def process( temporary_manifest_filepath = os.path.join(tmpdir, 'manifest.json') with open(temporary_manifest_filepath, 'w', encoding='utf-8') as fp: for audio_file in paths2audio_files: - entry = {'input_filepath': audio_file, 'duration': librosa.get_duration(path=audio_file)} + entry = {'input_filepath': audio_file, 'duration': librosa.get_duration(filename=audio_file)} fp.write(json.dumps(entry) + '\n') config = { diff --git a/requirements/requirements_asr.txt b/requirements/requirements_asr.txt index 8df86fa4679a..011862ad723b 100644 --- a/requirements/requirements_asr.txt +++ b/requirements/requirements_asr.txt @@ -5,7 +5,7 @@ ipywidgets jiwer kaldi-python-io kaldiio -librosa>=0.10.0 +librosa>=0.9.0 marshmallow matplotlib packaging diff --git a/tests/collections/asr/test_asr_rnnt_encdec_model.py b/tests/collections/asr/test_asr_rnnt_encdec_model.py index b466d09c460d..b86ff89d8d4a 100644 --- a/tests/collections/asr/test_asr_rnnt_encdec_model.py +++ b/tests/collections/asr/test_asr_rnnt_encdec_model.py @@ -641,6 +641,7 @@ def test_greedy_multi_decoding_stateless_decoder(self, greedy_class): partial_hyp = partial_hyp[0] _ = greedy(encoder_output=enc_out, encoded_lengths=enc_len, partial_hypotheses=partial_hyp) + @pytest.mark.pleasefixme @pytest.mark.skipif( not NUMBA_RNNT_LOSS_AVAILABLE, reason='RNNTLoss has not been compiled with appropriate numba version.', )