From 1254e8aee1e3200acc2b4752c6822bfc1a21b22f Mon Sep 17 00:00:00 2001
From: StevenH <hongfanmeng@gmail.com>
Date: 星期六, 26 十月 2024 12:19:07 +0800
Subject: [PATCH] optimize ComputeDecibel in fsmn-vad model by using numpy (#2174)
---
funasr/models/whisper/model.py | 9 ++++++++-
1 files changed, 8 insertions(+), 1 deletions(-)
diff --git a/funasr/models/whisper/model.py b/funasr/models/whisper/model.py
index 8e9245a..398eea3 100644
--- a/funasr/models/whisper/model.py
+++ b/funasr/models/whisper/model.py
@@ -7,7 +7,11 @@
import torch.nn.functional as F
from torch import Tensor
from torch import nn
+
import whisper
+
+# import whisper_timestamped as whisper
+
from funasr.utils.load_utils import load_audio_text_image_video, extract_fbank
from funasr.register import tables
@@ -24,6 +28,7 @@
@tables.register("model_classes", "Whisper-large-v1")
@tables.register("model_classes", "Whisper-large-v2")
@tables.register("model_classes", "Whisper-large-v3")
+@tables.register("model_classes", "Whisper-large-v3-turbo")
@tables.register("model_classes", "WhisperWarp")
class WhisperWarp(nn.Module):
def __init__(self, *args, **kwargs):
@@ -108,7 +113,9 @@
# decode the audio
options = whisper.DecodingOptions(**kwargs.get("DecodingOptions", {}))
- result = whisper.decode(self.model, speech, options)
+
+ result = whisper.decode(self.model, speech, options=options)
+ # result = whisper.transcribe(self.model, speech)
results = []
result_i = {"key": key[0], "text": result.text}
--
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