Dev gzf exp (#1705)

zhifu gao

2024-05-08 a7bc099548576d6d855a3837523f51cadd0e8910

 funasr/models/sense_voice/model.py

@@ -514,6 +514,20 @@
        self.beam_search.sos = sos_int
        self.beam_search.eos = eos_int[0]

        # Paramterts for rich decoding
        self.beam_search.emo_unk = tokenizer.encode(
            DecodingOptions.get("emo_unk_token", "<|SPECIAL_TOKEN_1|>"), allowed_special="all")[0]
        self.beam_search.emo_unk_score = 1
        self.beam_search.emo_tokens = tokenizer.encode(
            DecodingOptions.get("emo_target_tokens", "<|HAPPY|><|SAD|><|ANGRY|>"), allowed_special="all")
        self.beam_search.emo_scores = DecodingOptions.get("emo_target_threshold", [0.1, 0.1, 0.1])

        self.beam_search.event_bg_token = tokenizer.encode(
            DecodingOptions.get("gain_tokens_bg", "<|Speech|><|BGM|><|Applause|><|Laughter|>"), allowed_special="all")
        self.beam_search.event_ed_token = tokenizer.encode(
            DecodingOptions.get("gain_tokens_ed", "<|/Speech|><|/BGM|><|/Applause|><|/Laughter|>"), allowed_special="all")
        self.beam_search.event_score_ga = DecodingOptions.get("gain_tokens_score", [1, 1, 1, 1])

        encoder_out, encoder_out_lens = self.encode(
            speech[None, :, :].permute(0, 2, 1), speech_lengths
        )
@@ -843,6 +857,20 @@
        self.beam_search.sos = sos_int
        self.beam_search.eos = eos_int[0]

        # Paramterts for rich decoding
        self.beam_search.emo_unk = tokenizer.encode(
            DecodingOptions.get("emo_unk_token", "<|SPECIAL_TOKEN_1|>"), allowed_special="all")[0]
        self.beam_search.emo_unk_score = 1
        self.beam_search.emo_tokens = tokenizer.encode(
            DecodingOptions.get("emo_target_tokens", "<|HAPPY|><|SAD|><|ANGRY|>"), allowed_special="all")
        self.beam_search.emo_scores = DecodingOptions.get("emo_target_threshold", [0.1, 0.1, 0.1])

        self.beam_search.event_bg_token = tokenizer.encode(
            DecodingOptions.get("gain_tokens_bg", "<|Speech|><|BGM|><|Applause|><|Laughter|>"), allowed_special="all")
        self.beam_search.event_ed_token = tokenizer.encode(
            DecodingOptions.get("gain_tokens_ed", "<|/Speech|><|/BGM|><|/Applause|><|/Laughter|>"), allowed_special="all")
        self.beam_search.event_score_ga = DecodingOptions.get("gain_tokens_score", [1, 1, 1, 1])

        encoder_out, encoder_out_lens = self.encode(
            speech[None, :, :].permute(0, 2, 1), speech_lengths
        )