From 6f7e27eb7c2d0a7649ec8f14d167c8da8e29f906 Mon Sep 17 00:00:00 2001
From: jmwang66 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期二, 16 五月 2023 15:07:20 +0800
Subject: [PATCH] Merge pull request #518 from alibaba-damo-academy/dev_wjm2
---
funasr/datasets/large_datasets/dataset.py | 24 ++++++++++++++++++------
1 files changed, 18 insertions(+), 6 deletions(-)
diff --git a/funasr/datasets/large_datasets/dataset.py b/funasr/datasets/large_datasets/dataset.py
index 8c224d8..5df61fd 100644
--- a/funasr/datasets/large_datasets/dataset.py
+++ b/funasr/datasets/large_datasets/dataset.py
@@ -1,20 +1,20 @@
+import logging
import os
import random
-import numpy
from functools import partial
import torch
-import torchaudio
import torch.distributed as dist
+import torchaudio
from kaldiio import ReadHelper
from torch.utils.data import IterableDataset
from funasr.datasets.large_datasets.datapipes.batch import MaxTokenBucketizerIterDataPipe
from funasr.datasets.large_datasets.datapipes.filter import FilterIterDataPipe
from funasr.datasets.large_datasets.datapipes.map import MapperIterDataPipe
+from funasr.datasets.large_datasets.utils.clipping import clipping
from funasr.datasets.large_datasets.utils.filter import filter
from funasr.datasets.large_datasets.utils.padding import padding
-from funasr.datasets.large_datasets.utils.clipping import clipping
from funasr.datasets.large_datasets.utils.tokenize import tokenize
@@ -28,7 +28,8 @@
class AudioDataset(IterableDataset):
- def __init__(self, scp_lists, data_names, data_types, frontend_conf=None, shuffle=True, mode="train"):
+ def __init__(self, scp_lists, data_names, data_types, frontend_conf=None, shuffle=True, speed_perturb=None,
+ mode="train"):
self.scp_lists = scp_lists
self.data_names = data_names
self.data_types = data_types
@@ -40,6 +41,9 @@
self.world_size = 1
self.worker_id = 0
self.num_workers = 1
+ self.speed_perturb = speed_perturb
+ if self.speed_perturb is not None:
+ logging.info("Using speed_perturb: {}".format(speed_perturb))
def set_epoch(self, epoch):
self.epoch = epoch
@@ -124,9 +128,15 @@
if sampling_rate != self.frontend_conf["fs"]:
waveform = torchaudio.transforms.Resample(orig_freq=sampling_rate,
new_freq=self.frontend_conf["fs"])(waveform)
- sampling_rate = self.frontend_conf["fs"]
+ sampling_rate = self.frontend_conf["fs"]
waveform = waveform.numpy()
mat = waveform[0]
+ if self.speed_perturb is not None:
+ speed = random.choice(self.speed_perturb)
+ if speed != 1.0:
+ mat, _ = torchaudio.sox_effects.apply_effects_tensor(
+ torch.tensor(mat).view(1, -1), sampling_rate, [['speed', str(speed)], ['rate', str(sampling_rate)]])
+ mat = mat.view(-1).numpy()
sample_dict[data_name] = mat
sample_dict["sampling_rate"] = sampling_rate
if data_name == "speech":
@@ -168,6 +178,7 @@
bpe_tokenizer,
conf,
frontend_conf,
+ speed_perturb=None,
mode="train",
batch_mode="padding"):
scp_lists = read_lists(data_list_file)
@@ -196,7 +207,8 @@
data_names,
data_types,
frontend_conf=frontend_conf,
- shuffle=shuffle,
+ shuffle=shuffle,
+ speed_perturb=speed_perturb,
mode=mode,
)
--
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