| | |
|---|
| | | kwargs["frontend"] = frontend |
|---|
| | | # build model |
|---|
| | | model_class = tables.model_classes.get(kwargs["model"]) |
|---|
| | | model_conf = kwargs.get("model_conf", {}) |
|---|
| | | model_conf = {} |
|---|
| | | deep_update(model_conf, kwargs.get("model_conf", {})) |
|---|
| | | deep_update(model_conf, kwargs) |
|---|
| | | model = model_class(**model_conf, vocab_size=vocab_size) |
|---|
| | | model.to(device) |
|---|
| | |
|---|
| | | key = res[i]["key"] |
|---|
| | | vadsegments = res[i]["value"] |
|---|
| | | input_i = data_list[i] |
|---|
| | | speech = load_audio_text_image_video(input_i, fs=kwargs["frontend"].fs, audio_fs=kwargs.get("fs", 16000)) |
|---|
| | | fs = kwargs["frontend"].fs if hasattr(kwargs["frontend"], "fs") else 16000 |
|---|
| | | speech = load_audio_text_image_video(input_i, fs=fs, audio_fs=kwargs.get("fs", 16000)) |
|---|
| | | speech_lengths = len(speech) |
|---|
| | | n = len(vadsegments) |
|---|
| | | data_with_index = [(vadsegments[i], i) for i in range(n)] |
|---|
