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minor updates to utils.py

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marcoyang1998 2023-08-16 16:47:23 +08:00
parent 2091bb5f25
commit 73fa1651f0
1 changed files with 38 additions and 20 deletions
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58
egs/libriheavy/ASR/zipformer_prompt_asr/utils.py
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@ -35,36 +35,50 @@ def get_facebook_biasing_list(
return output return output
def get_rare_words(): def get_rare_words(subset: str, min_count: int):
txt_path = f"data/lang_bpe_500/transcript_words_{subset}.txt" txt_path = f"data/tmp/transcript_words_{subset}.txt"
rare_word_file = f"data/context_biasing/{subset}_rare_words_{min_count}.txt" rare_word_file = f"data/context_biasing/{subset}_rare_words_{min_count}.txt"
if os.path.exists(rare_word_file): if os.path.exists(rare_word_file):
print("File exists, do not proceed!") print("File exists, do not proceed!")
return return
with open(txt_path, "r") as file: print(f"Finding rare words in the manifest.")
words = file.read().upper().split() count_file = f"data/tmp/transcript_words_{subset}_count.txt"
if not os.path.exists(count_file):
with open(txt_path, "r") as file:
words = file.read().upper().split()
word_count = {}
for word in words:
word = remove_non_alphabetic(word, strict=False)
word = word.split()
for w in word:
if w not in word_count:
word_count[w] = 1
else:
word_count[w] += 1
with open(count_file, 'w') as fout:
for w in word_count:
fout.write(f"{w}\t{word_count[w]}")
else:
word_count = {} word_count = {}
for word in words: with open(count_file, 'r') as fin:
word = remove_non_alphabetic(word, strict=False) word_count = fin.read().split('\n')
if word not in word_count: word_count = [pair.split() for pair in word_count]
word_count[word] = 1
else:
word_count[word] += 1
print(f"A total of {len(word_count)} words appeared!") print(f"A total of {len(word_count)} words appeared!")
rare_words = [] rare_words = []
for k in word_count: for k in word_count:
if word_count[k] <= min_count: if int(word_count[k]) <= min_count:
rare_words.append(k+"\n") rare_words.append(k+"\n")
print(f"A total of {len(rare_words)} appeared <= 10 times") print(f"A total of {len(rare_words)} appeared <= {min_count} times")
with open(rare_word_file, 'w') as f: with open(rare_word_file, 'w') as f:
f.writelines(rare_words) f.writelines(rare_words)
def add_context_list_to_manifest(subset: str, min_count: int): def add_context_list_to_manifest(subset: str, min_count: int):
rare_words_file = f"data/context_biasing/{subset}_rare_words_{min_count}.txt" rare_words_file = f"data/context_biasing/{subset}_rare_words_{min_count}.txt"
manifest_dir = f"data/fbank/librilight_cuts_train_{subset}.jsonl.gz" manifest_dir = f"data/fbank/libriheavy_cuts_{subset}.jsonl.gz"
target_manifest_dir = manifest_dir.replace(".jsonl.gz", f"_with_context_list_min_count_{min_count}.jsonl.gz") target_manifest_dir = manifest_dir.replace(".jsonl.gz", f"_with_context_list_min_count_{min_count}.jsonl.gz")
if os.path.exists(target_manifest_dir): if os.path.exists(target_manifest_dir):
@ -82,7 +96,7 @@ def add_context_list_to_manifest(subset: str, min_count: int):
print(f"Loaded manifest from {manifest_dir}") print(f"Loaded manifest from {manifest_dir}")
def _add_context(c: Cut): def _add_context(c: Cut):
splits = remove_non_alphabetic(c.supervisions[0].text).upper().split() splits = remove_non_alphabetic(c.supervisions[0].texts[0], strict=False).upper().split()
found = [] found = []
for w in splits: for w in splits:
if w in rare_words: if w in rare_words:
@ -97,17 +111,21 @@ def add_context_list_to_manifest(subset: str, min_count: int):
def check(subset: str, min_count: int): def check(subset: str, min_count: int):
manifest_dir = f"data/fbank/librilight_cuts_train_{subset}_with_context_list_min_count_{min_count}.jsonl.gz" #manifest_dir = f"data/fbank/libriheavy_cuts_{subset}_with_context_list_min_count_{min_count}.jsonl.gz"
print("Calculating the stats over the manifest")
manifest_dir = f"data/fbank/libriheavy_cuts_{subset}_with_context_list_min_count_{min_count}.jsonl.gz"
cuts = load_manifest_lazy(manifest_dir) cuts = load_manifest_lazy(manifest_dir)
total_cuts = len(cuts) total_cuts = len(cuts)
has_context_list = [c.supervisions[0].context_list != "" for c in cuts] has_context_list = [c.supervisions[0].context_list != "" for c in cuts]
context_list_len = [len(c.supervisions[0].context_list.split()) for c in cuts]
print(f"{sum(has_context_list)}/{total_cuts} cuts have context list! ") print(f"{sum(has_context_list)}/{total_cuts} cuts have context list! ")
print(f"Average length of non-empty context list is {sum(context_list_len)/sum(has_context_list)}")
if __name__=="__main__": if __name__=="__main__":
#test_set = "test-clean" #test_set = "test-clean"
#get_facebook_biasing_list(test_set) #get_facebook_biasing_list(test_set)
#get_rare_words() subset = "medium"
subset = "small" min_count = 10
add_context_list_to_manifest(subset=subset) #get_rare_words(subset, min_count)
#add_context_list_to_manifest(subset=subset, min_count=min_count)
check(subset=subset, min_count=min_count)