Initial commit: FunASR Speech Recognition Toolkit

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

examples/industrial_data_pretraining/whisper/finetune.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+# Whisper Fine-tuning with FunASR
+#
+# This script fine-tunes OpenAI Whisper models on custom data using FunASR's training framework.
+# Supports: whisper-tiny, whisper-base, whisper-small, whisper-medium, whisper-large-v3
+#
+# Data format: JSONL with "audio" and "text" fields
+# {"key": "utt1", "source": "/path/to/audio.wav", "target": "transcription text"}
+
+export CUDA_VISIBLE_DEVICES=0,1
+
+model_name="Whisper-large-v3"
+train_data="data/train.jsonl"
+val_data="data/val.jsonl"
+output_dir="exp/whisper_finetune"
+
+python -m funasr.bin.train \
+    ++model="${model_name}" \
+    ++model_conf.hub="openai" \
+    ++train_data_set_list="${train_data}" \
+    ++valid_data_set_list="${val_data}" \
+    ++dataset_conf.batch_size=4 \
+    ++dataset_conf.num_workers=4 \
+    ++train_conf.output_dir="${output_dir}" \
+    ++train_conf.max_epoch=10 \
+    ++train_conf.lr=1e-5 \
+    ++train_conf.warmup_steps=500 \
+    ++optim="adam" \
+    ++optim_conf.lr=1e-5 \
+    ++scheduler="warmuplr" \
+    ++scheduler_conf.warmup_steps=500