import math from copy import deepcopy from random import random from typing import Union from unittest import TestCase from unittest.mock import Mock import numpy from voicevox_engine.acoustic_feature_extractor import OjtPhoneme from voicevox_engine.model import AccentPhrase, AudioQuery, Mora from voicevox_engine.synthesis_engine import SynthesisEngine # TODO: import from voicevox_engine.synthesis_engine.mora from voicevox_engine.synthesis_engine.synthesis_engine import ( mora_phoneme_list, pre_process, split_mora, to_flatten_moras, to_phoneme_data_list, unvoiced_mora_phoneme_list, ) def yukarin_s_mock(length: int, phoneme_list: numpy.ndarray, speaker_id: numpy.ndarray): result = [] # mockとしての適当な処理、特に意味はない for i in range(length): result.append(float(phoneme_list[i] * 0.5 + speaker_id)) return numpy.array(result) def yukarin_sa_mock( length: int, vowel_phoneme_list: numpy.ndarray, consonant_phoneme_list: numpy.ndarray, start_accent_list: numpy.ndarray, end_accent_list: numpy.ndarray, start_accent_phrase_list: numpy.ndarray, end_accent_phrase_list: numpy.ndarray, speaker_id: numpy.ndarray, ): result = [] # mockとしての適当な処理、特に意味はない for i in range(length): result.append( float( ( vowel_phoneme_list[0][i] + consonant_phoneme_list[0][i] + start_accent_list[0][i] + end_accent_list[0][i] + start_accent_phrase_list[0][i] + end_accent_phrase_list[0][i] ) * 0.5 + speaker_id ) ) return numpy.array(result)[numpy.newaxis] def decode_mock( length: int, phoneme_size: int, f0: numpy.ndarray, phoneme: numpy.ndarray, speaker_id: Union[numpy.ndarray, int], ): result = [] # mockとしての適当な処理、特に意味はない for i in range(length): # decode forwardはデータサイズがlengthの256倍になるのでとりあえず256回データをresultに入れる for _ in range(256): result.append( float( f0[i][0] * (numpy.where(phoneme[i] == 1)[0] / phoneme_size) + speaker_id ) ) return numpy.array(result) class MockCore: yukarin_s_forward = Mock(side_effect=yukarin_s_mock) yukarin_sa_forward = Mock(side_effect=yukarin_sa_mock) decode_forward = Mock(side_effect=decode_mock) def metas(self): return "" def supported_devices(self): return "" def is_model_loaded(self, speaker_id): return True class TestSynthesisEngine(TestCase): def setUp(self): super().setUp() self.str_list_hello_hiho = ( "sil k o N n i ch i w a pau h i h o d e s U sil".split() ) self.phoneme_data_list_hello_hiho = [ OjtPhoneme(phoneme=p, start=i, end=i + 1) for i, p in enumerate( "pau k o N n i ch i w a pau h i h o d e s U pau".split() ) ] self.accent_phrases_hello_hiho = [ AccentPhrase( moras=[ Mora( text="コ", consonant="k", consonant_length=0.0, vowel="o", vowel_length=0.0, pitch=0.0, ), Mora( text="ン", consonant=None, consonant_length=None, vowel="N", vowel_length=0.0, pitch=0.0, ), Mora( text="ニ", consonant="n", consonant_length=0.0, vowel="i", vowel_length=0.0, pitch=0.0, ), Mora( text="チ", consonant="ch", consonant_length=0.0, vowel="i", vowel_length=0.0, pitch=0.0, ), Mora( text="ワ", consonant="w", consonant_length=0.0, vowel="a", vowel_length=0.0, pitch=0.0, ), ], accent=5, pause_mora=Mora( text="、", consonant=None, consonant_length=None, vowel="pau", vowel_length=0.0, pitch=0.0, ), ), AccentPhrase( moras=[ Mora( text="ヒ", consonant="h", consonant_length=0.0, vowel="i", vowel_length=0.0, pitch=0.0, ), Mora( text="ホ", consonant="h", consonant_length=0.0, vowel="o", vowel_length=0.0, pitch=0.0, ), Mora( text="デ", consonant="d", consonant_length=0.0, vowel="e", vowel_length=0.0, pitch=0.0, ), Mora( text="ス", consonant="s", consonant_length=0.0, vowel="U", vowel_length=0.0, pitch=0.0, ), ], accent=1, pause_mora=None, ), ] core = MockCore() self.yukarin_s_mock = core.yukarin_s_forward self.yukarin_sa_mock = core.yukarin_sa_forward self.decode_mock = core.decode_forward self.synthesis_engine = SynthesisEngine( core=core, ) def test_to_flatten_moras(self): flatten_moras = to_flatten_moras(self.accent_phrases_hello_hiho) self.assertEqual( flatten_moras, self.accent_phrases_hello_hiho[0].moras + [self.accent_phrases_hello_hiho[0].pause_mora] + self.accent_phrases_hello_hiho[1].moras, ) def test_to_phoneme_data_list(self): phoneme_data_list = to_phoneme_data_list(self.str_list_hello_hiho) self.assertEqual(phoneme_data_list, self.phoneme_data_list_hello_hiho) def test_split_mora(self): consonant_phoneme_list, vowel_phoneme_list, vowel_indexes = split_mora( self.phoneme_data_list_hello_hiho ) self.assertEqual(vowel_indexes, [0, 2, 3, 5, 7, 9, 10, 12, 14, 16, 18, 19]) self.assertEqual( vowel_phoneme_list, [ OjtPhoneme(phoneme="pau", start=0, end=1), OjtPhoneme(phoneme="o", start=2, end=3), OjtPhoneme(phoneme="N", start=3, end=4), OjtPhoneme(phoneme="i", start=5, end=6), OjtPhoneme(phoneme="i", start=7, end=8), OjtPhoneme(phoneme="a", start=9, end=10), OjtPhoneme(phoneme="pau", start=10, end=11), OjtPhoneme(phoneme="i", start=12, end=13), OjtPhoneme(phoneme="o", start=14, end=15), OjtPhoneme(phoneme="e", start=16, end=17), OjtPhoneme(phoneme="U", start=18, end=19), OjtPhoneme(phoneme="pau", start=19, end=20), ], ) self.assertEqual( consonant_phoneme_list, [ None, OjtPhoneme(phoneme="k", start=1, end=2), None, OjtPhoneme(phoneme="n", start=4, end=5), OjtPhoneme(phoneme="ch", start=6, end=7), OjtPhoneme(phoneme="w", start=8, end=9), None, OjtPhoneme(phoneme="h", start=11, end=12), OjtPhoneme(phoneme="h", start=13, end=14), OjtPhoneme(phoneme="d", start=15, end=16), OjtPhoneme(phoneme="s", start=17, end=18), None, ], ) def test_pre_process(self): flatten_moras, phoneme_data_list = pre_process( deepcopy(self.accent_phrases_hello_hiho) ) mora_index = 0 phoneme_index = 1 self.assertEqual(phoneme_data_list[0], OjtPhoneme("pau", 0, 1)) for accent_phrase in self.accent_phrases_hello_hiho: moras = accent_phrase.moras for mora in moras: self.assertEqual(flatten_moras[mora_index], mora) mora_index += 1 if mora.consonant is not None: self.assertEqual( phoneme_data_list[phoneme_index], OjtPhoneme(mora.consonant, phoneme_index, phoneme_index + 1), ) phoneme_index += 1 self.assertEqual( phoneme_data_list[phoneme_index], OjtPhoneme(mora.vowel, phoneme_index, phoneme_index + 1), ) phoneme_index += 1 if accent_phrase.pause_mora: self.assertEqual(flatten_moras[mora_index], accent_phrase.pause_mora) mora_index += 1 self.assertEqual( phoneme_data_list[phoneme_index], OjtPhoneme("pau", phoneme_index, phoneme_index + 1), ) phoneme_index += 1 self.assertEqual( phoneme_data_list[phoneme_index], OjtPhoneme("pau", phoneme_index, phoneme_index + 1), ) def test_replace_phoneme_length(self): result = self.synthesis_engine.replace_phoneme_length( accent_phrases=deepcopy(self.accent_phrases_hello_hiho), speaker_id=1 ) # yukarin_sに渡される値の検証 yukarin_s_args = self.yukarin_s_mock.call_args[1] list_length = yukarin_s_args["length"] phoneme_list = yukarin_s_args["phoneme_list"] self.assertEqual(list_length, 20) self.assertEqual(list_length, len(phoneme_list)) numpy.testing.assert_array_equal( phoneme_list, numpy.array( [ 0, 23, 30, 4, 28, 21, 10, 21, 42, 7, 0, 19, 21, 19, 30, 12, 14, 35, 6, 0, ], dtype=numpy.int64, ), ) self.assertEqual(yukarin_s_args["speaker_id"], 1) # flatten_morasを使わずに愚直にaccent_phrasesにデータを反映させてみる true_result = deepcopy(self.accent_phrases_hello_hiho) index = 1 def result_value(i: int): return float(phoneme_list[i] * 0.5 + 1) for accent_phrase in true_result: moras = accent_phrase.moras for mora in moras: if mora.consonant is not None: mora.consonant_length = result_value(index) index += 1 mora.vowel_length = result_value(index) index += 1 if accent_phrase.pause_mora is not None: accent_phrase.pause_mora.vowel_length = result_value(index) index += 1 self.assertEqual(result, true_result) def test_replace_mora_pitch(self): # 空のリストでエラーを吐かないか empty_accent_phrases = [] self.assertEqual( self.synthesis_engine.replace_mora_pitch( accent_phrases=empty_accent_phrases, speaker_id=1 ), [], ) result = self.synthesis_engine.replace_mora_pitch( accent_phrases=deepcopy(self.accent_phrases_hello_hiho), speaker_id=1 ) # yukarin_saに渡される値の検証 yukarin_sa_args = self.yukarin_sa_mock.call_args[1] list_length = yukarin_sa_args["length"] vowel_phoneme_list = yukarin_sa_args["vowel_phoneme_list"][0] consonant_phoneme_list = yukarin_sa_args["consonant_phoneme_list"][0] start_accent_list = yukarin_sa_args["start_accent_list"][0] end_accent_list = yukarin_sa_args["end_accent_list"][0] start_accent_phrase_list = yukarin_sa_args["start_accent_phrase_list"][0] end_accent_phrase_list = yukarin_sa_args["end_accent_phrase_list"][0] self.assertEqual(list_length, 12) self.assertEqual(list_length, len(vowel_phoneme_list)) self.assertEqual(list_length, len(consonant_phoneme_list)) self.assertEqual(list_length, len(start_accent_list)) self.assertEqual(list_length, len(end_accent_list)) self.assertEqual(list_length, len(start_accent_phrase_list)) self.assertEqual(list_length, len(end_accent_phrase_list)) self.assertEqual(yukarin_sa_args["speaker_id"], 1) numpy.testing.assert_array_equal( vowel_phoneme_list, numpy.array( [ 0, 30, 4, 21, 21, 7, 0, 21, 30, 14, 6, 0, ] ), ) numpy.testing.assert_array_equal( consonant_phoneme_list, numpy.array( [ -1, 23, -1, 28, 10, 42, -1, 19, 19, 12, 35, -1, ] ), ) numpy.testing.assert_array_equal( start_accent_list, numpy.array([0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0]) ) numpy.testing.assert_array_equal( end_accent_list, numpy.array([0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0]) ) numpy.testing.assert_array_equal( start_accent_phrase_list, numpy.array([0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0]) ) numpy.testing.assert_array_equal( end_accent_phrase_list, numpy.array([0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0]) ) # flatten_morasを使わずに愚直にaccent_phrasesにデータを反映させてみる true_result = deepcopy(self.accent_phrases_hello_hiho) index = 1 def result_value(i: int): # unvoiced_mora_phoneme_listのPhoneme ID版 unvoiced_mora_phoneme_id_list = [ OjtPhoneme(p, 0, 0).phoneme_id for p in unvoiced_mora_phoneme_list ] if vowel_phoneme_list[i] in unvoiced_mora_phoneme_id_list: return 0 return ( vowel_phoneme_list[i] + consonant_phoneme_list[i] + start_accent_list[i] + end_accent_list[i] + start_accent_phrase_list[i] + end_accent_phrase_list[i] ) * 0.5 + 1 for accent_phrase in true_result: moras = accent_phrase.moras for mora in moras: mora.pitch = result_value(index) index += 1 if accent_phrase.pause_mora is not None: accent_phrase.pause_mora.pitch = result_value(index) index += 1 self.assertEqual(result, true_result) def synthesis_test_base(self, audio_query: AudioQuery): accent_phrases = audio_query.accent_phrases # decode forwardのために適当にpitchとlengthを設定し、リストで持っておく phoneme_length_list = [0.0] phoneme_id_list = [0] f0_list = [0.0] for accent_phrase in accent_phrases: moras = accent_phrase.moras for mora in moras: if mora.consonant is not None: mora.consonant_length = 0.1 phoneme_length_list.append(0.1) phoneme_id_list.append(OjtPhoneme(mora.consonant, 0, 0).phoneme_id) mora.vowel_length = 0.2 phoneme_length_list.append(0.2) phoneme_id_list.append(OjtPhoneme(mora.vowel, 0, 0).phoneme_id) if mora.vowel not in unvoiced_mora_phoneme_list: mora.pitch = 5.0 + random() f0_list.append(mora.pitch) if accent_phrase.pause_mora is not None: accent_phrase.pause_mora.vowel_length = 0.2 phoneme_length_list.append(0.2) phoneme_id_list.append(OjtPhoneme("pau", 0, 0).phoneme_id) f0_list.append(0.0) phoneme_length_list.append(0.0) phoneme_id_list.append(0) f0_list.append(0.0) phoneme_length_list[0] = audio_query.prePhonemeLength phoneme_length_list[-1] = audio_query.postPhonemeLength for i in range(len(phoneme_length_list)): phoneme_length_list[i] /= audio_query.speedScale result = self.synthesis_engine.synthesis(query=audio_query, speaker_id=1) # decodeに渡される値の検証 decode_args = self.decode_mock.call_args[1] list_length = decode_args["length"] self.assertEqual( list_length, int(sum([round(p * 24000 / 256) for p in phoneme_length_list])), ) num_phoneme = OjtPhoneme.num_phoneme # mora_phoneme_listのPhoneme ID版 mora_phoneme_id_list = [ OjtPhoneme(p, 0, 0).phoneme_id for p in mora_phoneme_list ] # numpy.repeatをfor文でやる f0 = [] phoneme = [] f0_index = 0 mean_f0 = [] for i, phoneme_length in enumerate(phoneme_length_list): f0_single = numpy.array(f0_list[f0_index], dtype=numpy.float32) * ( 2**audio_query.pitchScale ) for _ in range(int(round(phoneme_length * (24000 / 256)))): f0.append([f0_single]) phoneme_s = [] for _ in range(num_phoneme): phoneme_s.append(0) # one hot phoneme_s[phoneme_id_list[i]] = 1 phoneme.append(phoneme_s) # consonantとvowelを判別し、vowelであればf0_indexを一つ進める if phoneme_id_list[i] in mora_phoneme_id_list: if f0_single > 0: mean_f0.append(f0_single) f0_index += 1 mean_f0 = numpy.array(mean_f0, dtype=numpy.float32).mean() f0 = numpy.array(f0, dtype=numpy.float32) for i in range(len(f0)): if f0[i][0] != 0.0: f0[i][0] = (f0[i][0] - mean_f0) * audio_query.intonationScale + mean_f0 phoneme = numpy.array(phoneme, dtype=numpy.float32) # 乱数の影響で数値の位置がずれが生じるので、大半(4/5)があっていればよしとする # また、上の部分のint(round(phoneme_length * (24000 / 256)))の影響で # 本来のf0/phonemeとテスト生成したf0/phonemeの長さが変わることがあり、 # テスト生成したものが若干長くなることがあるので、本来のものの長さを基準にassertする assert_f0_count = 0 decode_f0 = decode_args["f0"] for i in range(len(decode_f0)): # 乱数の影響等で数値にずれが生じるので、10の-5乗までの近似値であれば許容する assert_f0_count += math.isclose(f0[i][0], decode_f0[i][0], rel_tol=10e-5) self.assertTrue(assert_f0_count >= int(len(decode_f0) / 5) * 4) assert_phoneme_count = 0 decode_phoneme = decode_args["phoneme"] for i in range(len(decode_phoneme)): assert_true_count = 0 for j in range(len(decode_phoneme[i])): assert_true_count += bool(phoneme[i][j] == decode_phoneme[i][j]) assert_phoneme_count += assert_true_count == num_phoneme self.assertTrue(assert_phoneme_count >= int(len(decode_phoneme) / 5) * 4) self.assertEqual(decode_args["speaker_id"], 1) # decode forwarderのmockを使う true_result = decode_mock(list_length, num_phoneme, f0, phoneme, 1) true_result *= audio_query.volumeScale # TODO: resampyの部分は値の検証しようがないので、パスする if audio_query.outputSamplingRate != 24000: return assert_result_count = 0 for i in range(len(true_result)): if audio_query.outputStereo: assert_result_count += math.isclose( true_result[i], result[i][0], rel_tol=10e-5 ) and math.isclose(true_result[i], result[i][1], rel_tol=10e-5) else: assert_result_count += math.isclose( true_result[i], result[i], rel_tol=10e-5 ) self.assertTrue(assert_result_count >= int(len(true_result) / 5) * 4) def test_synthesis(self): audio_query = AudioQuery( accent_phrases=deepcopy(self.accent_phrases_hello_hiho), speedScale=1.0, pitchScale=1.0, intonationScale=1.0, volumeScale=1.0, prePhonemeLength=0.1, postPhonemeLength=0.1, outputSamplingRate=24000, outputStereo=False, # このテスト内では使わないので生成不要 kana="", ) self.synthesis_test_base(audio_query) # speed scaleのテスト audio_query.speedScale = 1.2 self.synthesis_test_base(audio_query) # pitch scaleのテスト audio_query.pitchScale = 1.5 audio_query.speedScale = 1.0 self.synthesis_test_base(audio_query) # intonation scaleのテスト audio_query.pitchScale = 1.0 audio_query.intonationScale = 1.4 self.synthesis_test_base(audio_query) # volume scaleのテスト audio_query.intonationScale = 1.0 audio_query.volumeScale = 2.0 self.synthesis_test_base(audio_query) # pre/post phoneme lengthのテスト audio_query.volumeScale = 1.0 audio_query.prePhonemeLength = 0.5 audio_query.postPhonemeLength = 0.5 self.synthesis_test_base(audio_query) # output sampling rateのテスト audio_query.prePhonemeLength = 0.1 audio_query.postPhonemeLength = 0.1 audio_query.outputSamplingRate = 48000 self.synthesis_test_base(audio_query) # output stereoのテスト audio_query.outputSamplingRate = 24000 audio_query.outputStereo = True self.synthesis_test_base(audio_query)