Initial commit: FunASR Speech Recognition Toolkit

Add complete FunASR codebase including models, runtime, and documentation.

examples/industrial_data_pretraining/llm_asr/demo_speech2text.py

@@ -0,0 +1,52 @@
+#!/usr/bin/env python3
+# -*- encoding: utf-8 -*-
+# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
+#  MIT License  (https://opensource.org/licenses/MIT)
+
+import json
+import os
+import sys
+
+from funasr import AutoModel
+
+if len(sys.argv) > 1:
+    ckpt_dir = sys.argv[1]
+    ckpt_id = sys.argv[2]
+    jsonl = sys.argv[3]
+    output_dir = sys.argv[4]
+    device = sys.argv[5]
+else:
+    ckpt_dir = "/nfs/beinian.lzr/workspace/GPT-4o/Exp/exp6/5m-8gpu/exp6_speech2text_linear_ddp_0609"
+    ckpt_id = "model.pt.ep0.90000"
+    jsonl = "/nfs/beinian.lzr/workspace/GPT-4o/Data/Speech2Text/TestData/aishell1_test_speech2text.jsonl"
+    dataset = jsonl.split("/")[-1]
+    output_dir = os.path.join(ckpt_dir, f"inference-{ckpt_id}", dataset)
+    device = "cuda:0"
+
+
+model = AutoModel(
+    model=ckpt_dir,
+    init_param=f"{os.path.join(ckpt_dir, ckpt_id)}",
+    output_dir=output_dir,
+    device=device,
+    fp16=False,
+    bf16=False,
+    llm_dtype="bf16",
+)
+
+
+with open(jsonl, "r") as f:
+    lines = f.readlines()
+
+tearchforing = False
+for i, line in enumerate(lines):
+    data_dict = json.loads(line.strip())
+    data = data_dict["messages"]
+
+    res = model.generate(
+        input=[data],
+        tearchforing=tearchforing,
+        cache={},
+    )
+
+    print(res)