def update_symbols_and_text(sentences: SentenceList, sents_new_symbols: List[List[str]]):
symbols = SymbolIdDict.init_from_symbols(get_unique_items(sents_new_symbols))
for sentence, new_symbols in zip(sentences.items(), sents_new_symbols):
sentence.serialized_symbols = symbols.get_serialized_ids(new_symbols)
sentence.text = SymbolIdDict.symbols_to_text(new_symbols)
assert len(sentence.get_symbol_ids()) == len(new_symbols)
assert len(sentence.get_accent_ids()) == len(new_symbols)
return symbols, sentences
def test_sims_to_csv(self):
emb = torch.ones(size=(2, 3))
torch.nn.init.zeros_(emb[0])
sims = get_similarities(emb)
symbols = SymbolIdDict.init_from_symbols({"2", "1"})
res = sims_to_csv(sims, symbols)
self.assertEqual(2, len(res.index))
self.assertListEqual(['2', '<=>', '1', 'nan'], list(res.values[0]))
self.assertListEqual(['1', '<=>', '2', 'nan'], list(res.values[1]))
def test_plot_embeddings(self):
emb = torch.ones(size=(2, 3))
symbols = SymbolIdDict.init_from_symbols({})
text, plot2d, plot3d = plot_embeddings(symbols, emb, logging.getLogger())
self.assertEqual(2, len(text.index))
self.assertListEqual(['a', '<=>', 'b', '1.00'], list(text.values[0]))
self.assertListEqual(['b', '<=>', 'a', '1.00'], list(text.values[1]))
self.assertEqual("2D-Embeddings", plot2d.layout.title.text)
self.assertEqual("3D-Embeddings", plot3d.layout.title.text)
def test_get_similarities_is_sorted(self):
symbols = SymbolIdDict.init_from_symbols({"a", "b", "c"})
emb = np.zeros(shape=(3, 3))
emb[symbols.get_id("a")] = [0.5, 1.0, 0]
emb[symbols.get_id("b")] = [1.0, 0.6, 0]
emb[symbols.get_id("c")] = [1.0, 0.5, 0]
sims = get_similarities(emb)
self.assertEqual(3, len(sims))
self.assertEqual(symbols.get_id("b"), sims[symbols.get_id("a")][0][0])
self.assertEqual(symbols.get_id("c"), sims[symbols.get_id("a")][1][0])
self.assertEqual(symbols.get_id("b"), sims[symbols.get_id("c")][0][0])
self.assertEqual(symbols.get_id("a"), sims[symbols.get_id("c")][1][0])
self.assertEqual(symbols.get_id("c"), sims[symbols.get_id("b")][0][0])
self.assertEqual(symbols.get_id("a"), sims[symbols.get_id("b")][1][0])
def add_text(text: str, lang: Language, logger: Logger) -> Tuple[SymbolIdDict, SentenceList]:
res = SentenceList()
# each line is at least regarded as one sentence.
lines = text.split("\n")
all_sents = []
for line in lines:
sents = text_to_sentences(
text=line,
lang=lang,
logger=logger,
)
all_sents.extend(sents)
default_accent_id = 0
ipa_settings = IPAExtractionSettings(
ignore_tones=False,
ignore_arcs=False,
replace_unknown_ipa_by=DEFAULT_PADDING_SYMBOL,
)
sents_symbols: List[List[str]] = [text_to_symbols(
sent,
lang=lang,
ipa_settings=ipa_settings,
logger=logger,
) for sent in all_sents]
symbols = SymbolIdDict.init_from_symbols(get_unique_items(sents_symbols))
for i, sent_symbols in enumerate(sents_symbols):
sentence = Sentence(
sent_id=i + 1,
lang=lang,
serialized_symbols=symbols.get_serialized_ids(sent_symbols),
serialized_accents=serialize_list([default_accent_id] * len(sent_symbols)),
text=SymbolIdDict.symbols_to_text(sent_symbols),
original_text=SymbolIdDict.symbols_to_text(sent_symbols),
orig_lang=lang,
)
res.append(sentence)
return symbols, res
def test_preprocess(self):
datasets = {
"ljs":
(DsDataList([
DsData(0, "basename0", "speaker0", 0, "text0", "wavpath0",
Language.ENG),
DsData(1, "basename0", "speaker0", 0, "text0", "wavpath0",
Language.ENG),
DsData(2, "basename0", "speaker1", 1, "text0", "wavpath0",
Language.ENG),
]),
TextDataList([
TextData(0, "text_pre0", "1,2,3", Language.CHN),
TextData(1, "text_pre0", "1,2,3", Language.CHN),
TextData(2, "text_pre0", "1,2,3", Language.CHN),
]),
WavDataList([
WavData(0, "wavpath_pre0", 7.89, 22050),
WavData(1, "wavpath_pre0", 7.89, 22050),
WavData(2, "wavpath_pre0", 7.89, 22050),
]),
MelDataList([
MelData(0, "melpath_pre0", 80),
MelData(1, "melpath_pre0", 80),
MelData(2, "melpath_pre0", 80),
]), ["speaker0",
"speaker1"], SymbolIdDict.init_from_symbols({"a", "b"})),
"thchs": (DsDataList([
DsData(0, "basename0", "speaker0", 0, "text0", "wavpath0",
Language.ENG),
DsData(1, "basename0", "speaker1", 1, "text0", "wavpath0",
Language.ENG),
DsData(2, "basename0", "speaker1", 1, "text0", "wavpath0",
Language.ENG),
]),
TextDataList([
TextData(0, "text_pre0", "1,2,3", Language.CHN),
TextData(1, "text_pre0", "1,2,3", Language.CHN),
TextData(2, "text_pre0", "1,2,3", Language.CHN),
]),
WavDataList([
WavData(0, "wavpath_pre0", 7.89, 22050),
WavData(1, "wavpath_pre0", 7.89, 22050),
WavData(2, "wavpath_pre0", 7.89, 22050),
]),
MelDataList([
MelData(0, "melpath_pre0", 80),
MelData(1, "melpath_pre0", 80),
MelData(2, "melpath_pre0", 80),
]), ["speaker0", "speaker1"],
SymbolIdDict.init_from_symbols({"b", "c"}))
}
ds_speakers = {
("ljs", "speaker0"),
("thchs", "speaker1"),
}
whole, conv, speakers_id_dict = merge(datasets,
ds_speakers,
speakers_as_accents=False)
self.assertEqual(4, len(whole))
self.assertEqual(set({"a", "b", "c"}), set(conv.get_all_symbols()))
# TODO
self.assertEqual("1,2,3", whole[0].serialized_symbol_ids)
self.assertEqual("1,2,3", whole[1].serialized_symbol_ids)
self.assertEqual("1,3,4", whole[2].serialized_symbol_ids)
self.assertEqual("1,3,4", whole[3].serialized_symbol_ids)
self.assertEqual(["ljs,speaker0", "thchs,speaker1"],
speakers_id_dict.get_speakers())
def test_ds_dataset_to_merged_dataset(self):
ds = DsDataset(
name="ds",
accent_ids=AccentsDict.init_from_accents({"c", "d"}),
data=DsDataList([
DsData(
entry_id=1,
basename="basename",
speaker_id=2,
serialized_symbols="0,1",
gender=Gender.MALE,
lang=Language.GER,
serialized_accents="0,0",
wav_path="wav",
speaker_name="speaker",
text="text",
)
]),
mels=MelDataList([
MelData(
entry_id=1,
relative_mel_path="mel",
n_mel_channels=5,
)
]),
speakers=SpeakersDict.fromlist(["sp1", "sp2", "sp3"]),
symbol_ids=SymbolIdDict.init_from_symbols({"a", "b"}),
texts=TextDataList([
TextData(
entry_id=1,
lang=Language.IPA,
serialized_accent_ids="1,0",
serialized_symbol_ids="1,1",
text="text_new",
)
]),
wavs=WavDataList([
WavData(
entry_id=1,
duration=15,
sr=22050,
relative_wav_path="wav_new",
)
]),
)
res = ds_dataset_to_merged_dataset(ds)
self.assertEqual("ds", res.name)
self.assertEqual(2, len(res.accent_ids))
self.assertEqual(3, len(res.speakers))
self.assertEqual(2, len(res.symbol_ids))
self.assertEqual(1, len(res.items()))
first_entry = res.items()[0]
self.assertEqual(1, first_entry.entry_id)
self.assertEqual(Gender.MALE, first_entry.gender)
self.assertEqual("basename", first_entry.basename)
self.assertEqual(2, first_entry.speaker_id)
self.assertEqual(Language.IPA, first_entry.lang)
self.assertEqual("1,0", first_entry.serialized_accents)
self.assertEqual("1,1", first_entry.serialized_symbols)
self.assertEqual("wav_new", first_entry.wav_path)
self.assertEqual(15, first_entry.duration)
self.assertEqual(22050, first_entry.sampling_rate)
self.assertEqual("mel", first_entry.mel_path)
self.assertEqual(5, first_entry.n_mel_channels)
