From 1b978426040c836059cd0b941648e8515805b389 Mon Sep 17 00:00:00 2001
From: 北念 <lzr265946@alibaba-inc.com>
Date: 星期二, 23 七月 2024 11:45:43 +0800
Subject: [PATCH] add sensevoice scp2jsonl
---
funasr/datasets/audio_datasets/sensevoice2jsonl.py | 185 ++++++++++++++++++++++++++++++++++++++++++++++
data/list/train_text_language.txt | 4 +
data/list/train_emo.txt | 4 +
data/list/train_event.txt | 4 +
4 files changed, 197 insertions(+), 0 deletions(-)
diff --git a/data/list/train_emo.txt b/data/list/train_emo.txt
new file mode 100644
index 0000000..86e42b8
--- /dev/null
+++ b/data/list/train_emo.txt
@@ -0,0 +1,4 @@
+BAC009S0764W0121 <|NEUTRAL|>
+BAC009S0916W0489 <|NEUTRAL|>
+asr_example_cn_en <|NEUTRAL|>
+ID0012W0014 <|NEUTRAL|>
diff --git a/data/list/train_event.txt b/data/list/train_event.txt
new file mode 100644
index 0000000..3d1f212
--- /dev/null
+++ b/data/list/train_event.txt
@@ -0,0 +1,4 @@
+BAC009S0764W0121 <|Speech|>
+BAC009S0916W0489 <|Speech|>
+asr_example_cn_en <|Speech|>
+ID0012W0014 <|Speech|>
diff --git a/data/list/train_text_language.txt b/data/list/train_text_language.txt
new file mode 100644
index 0000000..6298ea0
--- /dev/null
+++ b/data/list/train_text_language.txt
@@ -0,0 +1,4 @@
+BAC009S0764W0121 <|zh|>
+BAC009S0916W0489 <|zh|>
+asr_example_cn_en <|zh|>
+ID0012W0014 <|en|>
diff --git a/funasr/datasets/audio_datasets/sensevoice2jsonl.py b/funasr/datasets/audio_datasets/sensevoice2jsonl.py
new file mode 100644
index 0000000..f58f43a
--- /dev/null
+++ b/funasr/datasets/audio_datasets/sensevoice2jsonl.py
@@ -0,0 +1,185 @@
+import os
+import json
+import torch
+import logging
+import hydra
+import re
+from omegaconf import DictConfig, OmegaConf
+import concurrent.futures
+import librosa
+import torch.distributed as dist
+from tqdm import tqdm
+
+
+def gen_jsonl_from_wav_text_list(
+ path, data_type_list=("source", "target"), jsonl_file_out: str = None, **kwargs
+):
+ try:
+ rank = dist.get_rank()
+ world_size = dist.get_world_size()
+ except:
+ rank = 0
+ world_size = 1
+
+ cpu_cores = os.cpu_count() or 1
+ print(f"convert wav.scp text to jsonl, ncpu: {cpu_cores}")
+ if rank == 0:
+ json_dict = {}
+ for data_type, data_file in zip(data_type_list, path):
+ json_dict[data_type] = {}
+ with open(data_file, "r") as f:
+
+ data_file_lists = f.readlines()
+ lines_for_each_th = (len(data_file_lists) - 1) // cpu_cores + 1
+ task_num = cpu_cores if len(data_file_lists) > cpu_cores else 1
+ # import pdb;pdb.set_trace()
+ if task_num > 1:
+ with concurrent.futures.ThreadPoolExecutor(max_workers=cpu_cores) as executor:
+
+ futures = [
+ executor.submit(
+ parse_context_length,
+ data_file_lists[
+ i * lines_for_each_th : (i + 1) * lines_for_each_th
+ ],
+ data_type,
+ i,
+ )
+ for i in range(task_num)
+ ]
+
+ for future in concurrent.futures.as_completed(futures):
+
+ json_dict[data_type].update(future.result())
+ else:
+ res = parse_context_length(data_file_lists, data_type)
+ json_dict[data_type].update(res)
+
+ if "text_language" not in data_type_list or "emo_target" not in data_type_list or "event_target" not in data_type_list:
+ from funasr import AutoModel
+
+ model_dir = "iic/SenseVoiceSmall"
+ model = AutoModel(
+ model=model_dir,
+ )
+
+ rich_dict = {}
+ for key in json_dict["source"].keys():
+ input_wav = json_dict["source"][key]["source"]
+ res = model.generate(
+ input=input_wav,
+ cache={},
+ language="auto", # "zn", "en", "yue", "ja", "ko", "nospeech"
+ use_itn=True,
+ )
+ text = res[0]["text"]
+ pattern = r"<\|[^|]+\|>"
+ matches = re.findall(pattern, text)
+ text_language, emo_target, event_target = matches[:3]
+ rich_dict[key] = [text_language, emo_target, event_target]
+
+
+ if "text_language" not in data_type_list:
+ data_type_list.append("text_language")
+ if "text_language" not in json_dict:
+ json_dict["text_language"] = {}
+ for key in json_dict["source"].keys():
+ json_dict["text_language"][key] = {}
+ json_dict["text_language"][key]["text_language"] = rich_dict[key][0]
+
+ if "emo_target" not in data_type_list:
+ data_type_list.append("emo_target")
+ if "emo_target" not in json_dict:
+ json_dict["emo_target"] = {}
+ for key in json_dict["source"].keys():
+ json_dict["emo_target"][key] = {}
+ json_dict["emo_target"][key]["emo_target"] = rich_dict[key][1]
+
+ if "event_target" not in data_type_list:
+ data_type_list.append("event_target")
+ if "event_target" not in json_dict:
+ json_dict["event_target"] = {}
+ for key in json_dict["source"].keys():
+ json_dict["event_target"][key] = {}
+ json_dict["event_target"][key]["event_target"] = rich_dict[key][2]
+
+ with open(jsonl_file_out, "w") as f:
+ for key in json_dict[data_type_list[0]].keys():
+ jsonl_line = {"key": key}
+ for data_file in data_type_list:
+ jsonl_line.update(json_dict[data_file][key])
+ jsonl_line = json.dumps(jsonl_line, ensure_ascii=False)
+ f.write(jsonl_line + "\n")
+ f.flush()
+ print(f"processed {len(json_dict[data_type_list[0]])} samples")
+
+ else:
+ pass
+
+ if world_size > 1:
+ dist.barrier()
+
+def contains_punctuation(s):
+ pattern = r'[!"#$%&\'()*+,-./:;<=>?@[\\]^_`{|}~]'
+ return re.search(pattern, s) is not None
+
+def parse_context_length(data_list: list, data_type: str, id=0):
+ pbar = tqdm(total=len(data_list), dynamic_ncols=True)
+ res = {}
+ for i, line in enumerate(data_list):
+ pbar.update(1)
+ pbar.set_description(f"cpu: {id}")
+ lines = line.strip().split(maxsplit=1)
+ key = lines[0]
+ line = lines[1] if len(lines) > 1 else ""
+ line = line.strip()
+ if os.path.exists(line):
+ waveform, _ = librosa.load(line, sr=16000)
+ sample_num = len(waveform)
+ context_len = int(sample_num / 16000 * 1000 / 10)
+ else:
+ context_len = len(line.split()) if " " in line else len(line)
+ if data_type == "source":
+ res[key] = {data_type: line, f"{data_type}_len": context_len}
+ elif data_type == "target":
+ punc = contains_punctuation(line)
+ if punc:
+ with_or_wo_itn = "<|withitn|>"
+ else:
+ with_or_wo_itn = "<|woitn|>"
+ res[key] = {data_type: line, f"{data_type}_len": context_len, "with_or_wo_itn": with_or_wo_itn}
+ else:
+ res[key] = {data_type: line}
+ return res
+
+
+@hydra.main(config_name=None, version_base=None)
+def main_hydra(cfg: DictConfig):
+
+ kwargs = OmegaConf.to_container(cfg, resolve=True)
+ print(kwargs)
+
+ scp_file_list = kwargs.get(
+ "scp_file_list",
+ ("/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt"),
+ )
+ if isinstance(scp_file_list, str):
+ scp_file_list = eval(scp_file_list)
+ data_type_list = kwargs.get("data_type_list", ("source", "target"))
+ jsonl_file_out = kwargs.get(
+ "jsonl_file_out", "/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl"
+ )
+ gen_jsonl_from_wav_text_list(
+ scp_file_list, data_type_list=data_type_list, jsonl_file_out=jsonl_file_out
+ )
+
+
+"""
+python -m funasr.datasets.audio_datasets.sensevoice2jsonl \
+++scp_file_list='["/Users/zhifu/funasr1.0/test_local/wav.scp", "/Users/zhifu/funasr1.0/test_local/text.txt", "/Users/zhifu/funasr1.0/test_local/text_language.txt", "/Users/zhifu/funasr1.0/test_local/emo_target.txt", "/Users/zhifu/funasr1.0/test_local/event_target.txt"]' \
+++data_type_list='["source", "target", "text_language", "emo_target", "event_target"]' \
+++jsonl_file_out=/Users/zhifu/funasr1.0/test_local/audio_datasets.jsonl
+"""
+
+if __name__ == "__main__":
+ main_hydra()
--
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