| import torch | |
| from transformers import AutoModel, AutoTokenizer | |
| repo_id = "humanify/ARAG_embedding_pretrain" | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| tokenizer = AutoTokenizer.from_pretrained(repo_id, trust_remote_code=True) | |
| model = AutoModel.from_pretrained( | |
| repo_id, | |
| trust_remote_code=True, | |
| torch_dtype=torch.float32, | |
| ).to(device).eval() | |
| model.set_tokenizer(tokenizer) | |
| QUERY_INSTRUCTION = "Based on the question asked in the text query and context in the audio query, retrieve the relevant text document associated with that question." | |
| DOC_INSTRUCTION = "Represent the user's input." | |
| # case 1 | |
| # expect [0-1match, 2-3match] | |
| # 模型正确区分出性别 | |
| # tensor([[0.5530, 0.4304], | |
| # [0.6178, 0.4669], | |
| # [0.3870, 0.6268], | |
| # [0.4139, 0.6821]], device='cuda:0') | |
| # tensor([[1.0000, 0.8968, 0.7887, 0.7221], | |
| # [0.8968, 1.0000, 0.7567, 0.7600], | |
| # [0.7887, 0.7567, 1.0000, 0.9216], | |
| # [0.7221, 0.7600, 0.9216, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "What is the gender of speaker in this audio?", | |
| # "What is the gender of speaker in this audio?", | |
| # "What is the gender of speaker in this audio?", | |
| # "What is the gender of speaker in this audio?", | |
| # ] | |
| # query_audio = ["./samples/en_male_music.wav", "./samples/en_male.wav", | |
| # "./samples/en_female_music.wav", "./samples/en_female.wav"] | |
| # case 2 | |
| # expect [0-2match, 1-3match] | |
| # 测试显示模型是可以区分出是否有背景音乐的 | |
| # tensor([[0.4247, 0.1398], | |
| # [0.2891, 0.1501], | |
| # [0.2446, 0.3100], | |
| # [0.2502, 0.3032]], device='cuda:0') | |
| # tensor([[1.0000, 0.7550, 0.6976, 0.6746], | |
| # [0.7550, 1.0000, 0.7014, 0.6887], | |
| # [0.6976, 0.7014, 1.0000, 0.8886], | |
| # [0.6746, 0.6887, 0.8886, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "Describe the background noise of this audio?", | |
| # "Describe the background noise of this audio?", | |
| # "Describe the background noise of this audio?", | |
| # "Describe the background noise of this audio?", | |
| # ] | |
| # query_audio = ["./samples/en_male_music.wav", "./samples/en_female_music.wav", | |
| # "./samples/en_male.wav", "./samples/en_female.wav"] | |
| # case 3 | |
| # expect [0-2match, 1-3match] | |
| # 模型具有quality分辨能力 | |
| # tensor([[0.4325, 0.3912], | |
| # [0.4801, 0.4459], | |
| # [0.4836, 0.4986], | |
| # [0.4723, 0.4741]], device='cuda:0') | |
| # tensor([[1.0000, 0.9511, 0.9240, 0.8633], | |
| # [0.9511, 1.0000, 0.9416, 0.8835], | |
| # [0.9240, 0.9416, 1.0000, 0.9293], | |
| # [0.8633, 0.8835, 0.9293, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "Describe the quality of the audio.", | |
| # "Describe the quality of the audio.", | |
| # "Describe the quality of the audio.", | |
| # "Describe the quality of the audio.", | |
| # ] | |
| # query_audio = ["./samples/en_male_music.wav", "./samples/en_male.wav", | |
| # "./samples/en_female_music.wav", "./samples/en_female.wav"] | |
| # case 4-1 | |
| # expect [1-3match] | |
| # query_text = [ | |
| # "Describe the speech content and topic.", | |
| # "Describe the speech content and topic.", | |
| # "Describe the speech content and topic.", | |
| # "Describe the speech content and topic.", | |
| # ] | |
| # query_audio = ["./samples/en_male_sunny.wav", "./samples/en_male.wav", | |
| # "./samples/en_female_sunny.wav", "./samples/en_female.wav"] | |
| # case 4-2 | |
| # expect [1-3match] | |
| # 模型可以正确区分出来音频中是否包含某个单词 | |
| # tensor([[0.7353, 0.4429], | |
| # [0.7130, 0.4250], | |
| # [0.5905, 0.6196], | |
| # [0.5303, 0.7002]], device='cuda:0') | |
| # tensor([[1.0000, 0.9781, 0.8920, 0.7941], | |
| # [0.9781, 1.0000, 0.9070, 0.8146], | |
| # [0.8920, 0.9070, 1.0000, 0.9668], | |
| # [0.7941, 0.8146, 0.9668, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "Does the speaker mention the word 'sunny' in the audio?", | |
| # "Does the speaker mention the word 'sunny' in the audio?", | |
| # "Does the speaker mention the word 'sunny' in the audio?", | |
| # "Does the speaker mention the word 'sunny' in the audio?", | |
| # ] | |
| # query_audio = ["./samples/en_male_sunny.wav", "./samples/en_female_sunny.wav", | |
| # "./samples/en_male.wav", "./samples/en_female.wav"] | |
| # case 5 | |
| # expect [0-1 match] | |
| # 模型具备区分动物叫声的能力，结果显示如下： | |
| # tensor([[0.7022, 0.4406, 0.4651], | |
| # [0.7497, 0.3858, 0.4209], | |
| # [0.3636, 0.4995, 0.3304], | |
| # [0.4793, 0.2937, 0.7720]], device='cuda:0') | |
| # tensor([[1.0000, 0.9535, 0.6508, 0.7476], | |
| # [0.9535, 1.0000, 0.5688, 0.6673], | |
| # [0.6508, 0.5688, 1.0000, 0.5568], | |
| # [0.7476, 0.6673, 0.5568, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "What type of animal is this?", | |
| # "What type of animal is this?", | |
| # "What type of animal is this?", | |
| # "What type of animal is this?", | |
| # ] | |
| # query_audio = ["./samples/animal_cow_1moo.wav", "./samples/animal_cow_5moo.wav", | |
| # "./samples/animal_lion.wav", "./samples/animal_rooster.wav"] | |
| # case 6 | |
| # expect [0-2 match, 1-3 match] | |
| # 模型能区分出中文和英文 | |
| # 汉语和英语 | |
| # 第一个矩阵结果正确，第二个矩阵有点问题 | |
| # tensor([[0.4100, 0.2334], | |
| # [0.4451, 0.2417], | |
| # [0.3379, 0.3609], | |
| # [0.3997, 0.4074]], device='cuda:0') | |
| # tensor([[1.0000, 0.9034, 0.8573, 0.7466], | |
| # [0.9034, 1.0000, 0.7729, 0.7808], | |
| # [0.8573, 0.7729, 1.0000, 0.8199], | |
| # [0.7466, 0.7808, 0.8199, 1.0000]], device='cuda:0') | |
| # 法语和英语，完全没有问题 | |
| # tensor([[0.4100, 0.3098], | |
| # [0.4411, 0.3229], | |
| # [0.3494, 0.4212], | |
| # [0.3523, 0.4130]], device='cuda:0') | |
| # tensor([[1.0000, 0.9030, 0.8696, 0.8591], | |
| # [0.9030, 1.0000, 0.7874, 0.8468], | |
| # [0.8696, 0.7874, 1.0000, 0.9654], | |
| # [0.8591, 0.8468, 0.9654, 1.0000]], device='cuda:0') | |
| # 英语和西班牙语，完全没有问题 | |
| # tensor([[0.4100, 0.3012], | |
| # [0.4411, 0.3069], | |
| # [0.3274, 0.3698], | |
| # [0.3249, 0.3558]], device='cuda:0') | |
| # tensor([[1.0000, 0.9030, 0.8591, 0.8590], | |
| # [0.9030, 1.0000, 0.7775, 0.8208], | |
| # [0.8591, 0.7775, 1.0000, 0.9739], | |
| # [0.8590, 0.8208, 0.9739, 1.0000]], device='cuda:0') | |
| # 法语和西班牙语，完全没有问题 | |
| # tensor([[0.4212, 0.2785], | |
| # [0.4170, 0.2737], | |
| # [0.2793, 0.3698], | |
| # [0.2721, 0.3558]], device='cuda:0') | |
| # tensor([[1.0000, 0.9661, 0.8730, 0.8688], | |
| # [0.9661, 1.0000, 0.8493, 0.8726], | |
| # [0.8730, 0.8493, 1.0000, 0.9739], | |
| # [0.8688, 0.8726, 0.9739, 1.0000]], device='cuda:0') | |
| # 法语和汉语，完全没问题 | |
| # tensor([[0.4212, 0.2278], | |
| # [0.4130, 0.2353], | |
| # [0.2986, 0.3609], | |
| # [0.3602, 0.4074]], device='cuda:0') | |
| # tensor([[1.0000, 0.9654, 0.7965, 0.6456], | |
| # [0.9654, 1.0000, 0.7990, 0.7011], | |
| # [0.7965, 0.7990, 1.0000, 0.8199], | |
| # [0.6456, 0.7011, 0.8199, 1.0000]], device='cuda:0') | |
| # 西班牙语和汉语，完全没问题 | |
| # tensor([[0.3698, 0.1813], | |
| # [0.3558, 0.1784], | |
| # [0.2814, 0.3609], | |
| # [0.3257, 0.4074]], device='cuda:0') | |
| # tensor([[1.0000, 0.9739, 0.7871, 0.6249], | |
| # [0.9739, 1.0000, 0.7837, 0.6546], | |
| # [0.7871, 0.7837, 1.0000, 0.8199], | |
| # [0.6249, 0.6546, 0.8199, 1.0000]], device='cuda:0') | |
| query_text = [ | |
| "Describe the language of the speaker.", | |
| "Describe the language of the speaker.", | |
| "Describe the language of the speaker.", | |
| "Describe the language of the speaker." | |
| ] | |
| query_audio = ["./samples/spanish_male.wav", "./samples/spanish_female.wav", | |
| "./samples/chinese_male.wav", "./samples/zh_female.wav"] | |
| # case 7 | |
| # expect [0-1 match] + [2-3 match] | |
| # 测试结果显示模型不具备区分出说话者语速快慢的能力 | |
| # query_text = [ | |
| # "Describe the speaking rate of the speaker.", | |
| # "Describe the speaking rate of the speaker.", | |
| # "Describe the speaking rate of the speaker.", | |
| # "Describe the speaking rate of the speaker." | |
| # ] | |
| # query_audio = ["./samples/female_fast_4.wav", "./samples/female_fast.wav", | |
| # "./samples/male_slow.wav", "./samples/female_slow.wav"] | |
| # case 8 | |
| # expect [0->one, 1->two] | |
| # 测试结果显示模型无法区分出声音不同类别的能力 | |
| # query_text = [ | |
| # "How many distinct sound types are present in this audio?", | |
| # "How many distinct sound types are present in this audio?", | |
| # "How many distinct sound types are present in this audio?", | |
| # "How many distinct sound types are present in this audio?" | |
| # ] | |
| # query_audio = [ | |
| # "./samples/one_type_sound.flac", "./samples/one_type_sound_2.flac", | |
| # "./samples/two_type_sound.flac", "./samples/two_type_sound_2.flac", | |
| # ] | |
| # case 9 | |
| # expect [0-1 match] + [2-3 match] | |
| # 测试结果显示模型具备对话语类型/语义的判断，结果如下所示。 | |
| # tensor([[0.3587, 0.2188], | |
| # [0.3793, 0.2482], | |
| # [0.2806, 0.3153], | |
| # [0.2676, 0.3588]], device='cuda:0') | |
| # tensor([[1.0000, 0.9275, 0.6241, 0.5684], | |
| # [0.9275, 1.0000, 0.7433, 0.6704], | |
| # [0.6241, 0.7433, 1.0000, 0.7269], | |
| # [0.5684, 0.6704, 0.7269, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "Identify the utterance type of this speech.", | |
| # "Identify the utterance type of this speech.", | |
| # "Identify the utterance type of this speech.", | |
| # "Identify the utterance type of this speech." | |
| # ] | |
| # query_audio = ["./samples/male_statement.wav", "./samples/female_statement.wav", | |
| # "./samples/male_question.wav", "./samples/female_question.wav"] | |
| # # case 10 | |
| # # expect | |
| # # 测试结果显示模型可以区分出音频是one-speaker还是two-speaker，结果如下所示。 | |
| # # tensor([[0.7003, 0.6864], | |
| # # [0.7050, 0.6986], | |
| # # [0.3909, 0.7932], | |
| # # [0.4326, 0.8110]], device='cuda:0') | |
| # # tensor([[1.0000, 0.9369, 0.7105, 0.7634], | |
| # # [0.9369, 1.0000, 0.7473, 0.7579], | |
| # # [0.7105, 0.7473, 1.0000, 0.8984], | |
| # # [0.7634, 0.7579, 0.8984, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "How many speakers in this audio?", | |
| # "How many speakers in this audio?", | |
| # "How many speakers in this audio?", | |
| # "How many speakers in this audio?", | |
| # ] | |
| # query_audio = [ | |
| # "./samples/en_male.wav", "./samples/en_female.wav", | |
| # "./samples/two_speaker.flac", "./samples/two_speaker_2.flac", | |
| # ] | |
| # case 11-1(说话) | |
| # expect | |
| # 测试结果如下所示。低音全都是用的male，可能有点不够solid。query-doc矩阵没问题，但是query-query矩阵有问题。 | |
| # tensor([[0.4330, 0.4321], | |
| # [0.4118, 0.3743], | |
| # [0.3756, 0.3932], | |
| # [0.4046, 0.4489]], device='cuda:0') | |
| # tensor([[1.0000, 0.9168, 0.9511, 0.9505], | |
| # [0.9168, 1.0000, 0.9212, 0.9323], | |
| # [0.9511, 0.9212, 1.0000, 0.9565], | |
| # [0.9505, 0.9323, 0.9565, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "Is the speaker's tone high or low?", | |
| # "Is the speaker's tone high or low?", | |
| # "Is the speaker's tone high or low?", | |
| # "Is the speaker's tone high or low?" | |
| # ] | |
| # query_audio = [ | |
| # "./samples/female_speech_high_1.wav", "./samples/male_speech_high_1.wav", | |
| # "./samples/male_speech_low_1.wav", "./samples/male_speech_low_2.wav" | |
| # ] | |
| # case 11-2(唱歌) | |
| # expect | |
| # 测试结果如下所示。低音全都是用的male，可能有点不够solid。 | |
| # tensor([[0.4901, 0.3206], | |
| # [0.4875, 0.3638], | |
| # [0.4354, 0.4760], | |
| # [0.4144, 0.4296]], device='cuda:0') | |
| # tensor([[1.0000, 0.9399, 0.8666, 0.8854], | |
| # [0.9399, 1.0000, 0.9261, 0.9368], | |
| # [0.8666, 0.9261, 1.0000, 0.9752], | |
| # [0.8854, 0.9368, 0.9752, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "Is the speaker's tone high or low?", | |
| # "Is the speaker's tone high or low?", | |
| # "Is the speaker's tone high or low?", | |
| # "Is the speaker's tone high or low?" | |
| # ] | |
| # query_audio = [ | |
| # "./samples/female_sing_high_1.wav", "./samples/male_sing_high_1.wav", | |
| # "./samples/male_sing_low_1.wav", "./samples/male_sing_low_2.wav" | |
| # ] | |
| # case 12 | |
| # expect [0-1 -> outdoor, 2-3 -> indoor] | |
| # 测试结果显示模型无法区分出模型是在室内还是室外发生 | |
| # query_text = [ | |
| # "Where is this audio most likely recorded?", | |
| # "Where is this audio most likely recorded?", | |
| # "Where is this audio most likely recorded?", | |
| # "Where is this audio most likely recorded?" | |
| # ] | |
| # query_audio = ["./samples/male_outdoor.wav", "./samples/female_outdoor.wav", | |
| # "./samples/indoor.flac", "./samples/indoor2.flac"] | |
| # # case 13 | |
| # # expect | |
| # 测试结果显示模型能够区分出情感差异，结果如下所示。 | |
| # tensor([[0.3226, 0.1865], | |
| # [0.4463, 0.2482], | |
| # [0.4102, 0.4539], | |
| # [0.3474, 0.4925]], device='cuda:0') | |
| # tensor([[1.0000, 0.7824, 0.5576, 0.5138], | |
| # [0.7824, 1.0000, 0.6224, 0.5177], | |
| # [0.5576, 0.6224, 1.0000, 0.8121], | |
| # [0.5138, 0.5177, 0.8121, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "What is the emotion of the speaker?", | |
| # "What is the emotion of the speaker?", | |
| # "What is the emotion of the speaker?", | |
| # "What is the emotion of the speaker?" | |
| # ] | |
| # query_audio = [ | |
| # "./samples/people_happy_1.flac", "./samples/people_happy_2.flac", | |
| # "./samples/people_cry_1.flac", "./samples/female_sad_1.wav" | |
| # ] | |
| # # case 14 | |
| # # expect [0->child, 1->adult] | |
| # # 测试结果如下所示，显示模型具备能力区分说话者的大致年龄。但是两个young都是用的boy； | |
| # # 如果用young_girl.wav的话, 第一个矩阵没问题，第二个矩阵有问题。 | |
| # # tensor([[0.5183, 0.5019], | |
| # # [0.5069, 0.4590], | |
| # # [0.2864, 0.5422], | |
| # # [0.3039, 0.5131]], device='cuda:0') | |
| # # tensor([[1.0000, 0.9227, 0.7293, 0.7653], | |
| # # [0.9227, 1.0000, 0.6910, 0.7291], | |
| # # [0.7293, 0.6910, 1.0000, 0.8695], | |
| # # [0.7653, 0.7291, 0.8695, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "Estimate the age of the speaker.", | |
| # "Estimate the age of the speaker.", | |
| # "Estimate the age of the speaker.", | |
| # "Estimate the age of the speaker." | |
| # ] | |
| # query_audio = [ | |
| # "./samples/young_boy_1.flac", "./samples/young_boy_2.wav", | |
| # "./samples/adult_man.flac", "./samples/adult_woman.flac" | |
| # ] | |
| # case 15 | |
| # 测试结果显示模型可以区分出不同的英语口音，结果如下所示。其中第二个矩阵中有点不够solid | |
| # tensor([[0.7703, 0.7582], | |
| # [0.7267, 0.7185], | |
| # [0.7237, 0.7307], | |
| # [0.7646, 0.7759]], device='cuda:0') | |
| # tensor([[1.0000, 0.9324, 0.9442, 0.9598], | |
| # [0.9324, 1.0000, 0.9827, 0.9704], | |
| # [0.9442, 0.9827, 1.0000, 0.9857], | |
| # [0.9598, 0.9704, 0.9857, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "Identify the English accent of the speaker.", | |
| # "Identify the English accent of the speaker.", | |
| # "Identify the English accent of the speaker.", | |
| # "Identify the English accent of the speaker." | |
| # ] | |
| # query_audio = ["./samples/male_america_english.wav", "./samples/female_america_english.wav", | |
| # "./samples/male_british_english.wav", "./samples/female_british_english.wav"] | |
| # # case 16 | |
| # # expect | |
| # # 测试结果显示模型可以区分出飞机引擎声和大巴引擎声，结果如下所示 | |
| # # tensor([[0.4200, 0.2822], | |
| # # [0.5744, 0.2713], | |
| # # [0.2183, 0.3696], | |
| # # [0.2527, 0.3816]], device='cuda:0') | |
| # # tensor([[1.0000, 0.8755, 0.7497, 0.7796# [0.6261, 0.5706, 1.0000, 0.7327], | |
| # [0.4892, 0.5031, 0.7327, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "What is the source of this sound?", | |
| # "What is the source of this sound?", | |
| # "What is the source of this sound?", | |
| # "What is the source of this sound?" | |
| # ] | |
| # query_audio = ["./samples/rainy.wav", "./samples/rainy_2.flac", | |
| # "./samples/wind_2.flac", "./samples/wind.flac"] | |
| # case 18 | |
| # expect | |
| # 测试结果显示模型具备对说话者的计数能力； | |
| # 3-speaker/4-speaker测试结果如下, query-doc矩阵没问题，query-query矩阵有点小问题 | |
| # tensor([[0.4325, 0.3912], | |
| # [0.4801, 0.4459], | |
| # [0.4836, 0.4986], | |
| # [0.4723, 0.4741]], device='cuda:0') | |
| # tensor([[1.0000, 0.9511, 0.9240, 0.8633], | |
| # [0.9511, 1.0000, 0.9416, 0.8835], | |
| # [0.9240, 0.9416, 1.0000, 0.9293], | |
| # [0.8633, 0.8835, 0.9293, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "What's the number of participants in the current conversation?", | |
| # "What's the number of participants in the current conversation?", | |
| # "What's the number of participants in the current conversation?", | |
| # "What's the number of participants in the current conversation?" | |
| # ] | |
| # query_audio = [ | |
| # "./samples/three_speaker_2.wav", "./samples/three_speaker.wav", | |
| # "./samples/four_speaker.wav", "./samples/four_speaker_3.wav", | |
| # ] | |
| # case 19 | |
| # 测试结果显示不具备音乐风格识别能力 | |
| # query_text = [ | |
| # "What is the music style in the audio?", | |
| # "What is the music style in the audio?", | |
| # "What is the music style in the audio?", | |
| # "What is the music style in the audio?" | |
| # ] | |
| # query_audio = [ | |
| # "./samples/hiphop_1.flac", "./samples/hiphop_2.flac", | |
| # "./samples/classical_1.flac", "./samples/classical_2.flac", | |
| # ] | |
| # case 20 | |
| # 测试结果显示模型具备识别乐器声音的能力 | |
| # tensor([[0.4882, 0.3500], | |
| # [0.4124, 0.3477], | |
| # [0.3047, 0.6171], | |
| # [0.4425, 0.5910]], device='cuda:0') | |
| # tensor([[1.0000, 0.8528, 0.7110, 0.8001], | |
| # [0.8528, 1.0000, 0.7338, 0.7728], | |
| # [0.7110, 0.7338, 1.0000, 0.9112], | |
| # [0.8001, 0.7728, 0.9112, 1.0000]], device='cuda:0') | |
| # query_text = [ | |
| # "What musical instrument is producing the sound?", | |
| # "What musical instrument is producing the sound?", | |
| # "What musical instrument is producing the sound?", | |
| # "What musical instrument is producing the sound?" | |
| # ] | |
| # query_audio = [ | |
| # "./samples/piano_3.flac", "./samples/piano_2.flac", | |
| # "./samples/guitar_1.flac", "./samples/guitar_2.flac", | |
| # ] | |
| # case 21 | |
| # 测试显示模型无法计数说话中单词的数量 | |
| # query_text = [ | |
| # "How many times does the word 'said' appear in the audio?", | |
| # "How many times does the word 'beautiful' appear in the audio?", | |
| # "How many times does the word 'fate' appear in the audio?", | |
| # "How many times does the word 'ninty' appear in the audio?" | |
| # ] | |
| # query_audio = [ | |
| # "./samples/1_said.wav", "./samples/1_beautiful.wav", | |
| # "./samples/1_fate.wav", "./samples/3_ninty_nine.wav", | |
| # ] | |
| # case 22 | |
| # 测试显示模型是否具备计数铃声和鼓声的能力 | |
| # query_text = [ | |
| # "How many times does the sound appear in the audio?", | |
| # "How many times does the sound appear in the audio?", | |
| # "How many times does the sound appear in the audio?", | |
| # "How many times does the sound appear in the audio?" | |
| # ] | |
| # query_audio = [ | |
| # "./samples/2_drumbeat.wav", "./samples/2_ringtone.wav", | |
| # "./samples/6_drumbeat.wav", "./samples/6_ringtone.wav" | |
| # ] | |
| # ---- | |
| # doc_text = [ | |
| # "male", | |
| # "female", | |
| # ] | |
| # doc_text = [ | |
| # "music", | |
| # "nothing", | |
| # ] | |
| # doc_text = [ | |
| # "High-quality", | |
| # "Low-quality", | |
| # ] | |
| # doc_text = [ | |
| # "yes", | |
| # "no", | |
| # ] | |
| # doc_text = [ | |
| # "cow", | |
| # "lion", | |
| # "rooster", | |
| # ] | |
| doc_text = [ | |
| "spanish", | |
| "chinese", | |
| ] | |
| # doc_text = [ | |
| # "fast", | |
| # "slow", | |
| # ] | |
| # doc_text = [ | |
| # "one type", | |
| # "two types", | |
| # ] | |
| # doc_text = [ | |
| # "statement", | |
| # "question", | |
| # ] | |
| # doc_text = [ | |
| # "one speaker", | |
| # "two speakers", | |
| # ] | |
| # doc_text = [ | |
| # "high", | |
| # "low", | |
| # ] | |
| # doc_text = [ | |
| # "outdoor", | |
| # "indoor", | |
| # ] | |
| # doc_text = [ | |
| # "happy", | |
| # "sad", | |
| # ] | |
| # doc_text = [ | |
| # "child", | |
| # "adult", | |
| # ] | |
| # doc_text = [ | |
| # "American accent", | |
| # "British accent", | |
| # ] | |
| # doc_text = [ | |
| # "helicopter engine", | |
| # "car engine", | |
| # ] | |
| # doc_text = [ | |
| # "rain", | |
| # "wind", | |
| # ] | |
| # doc_text = [ | |
| # "hiphop", | |
| # "classical", | |
| # ] | |
| # doc_text = [ | |
| # "three persons", | |
| # "four persons", | |
| # ] | |
| # doc_text = [ | |
| # "piano", | |
| # "guitar", | |
| # ] | |
| # doc_text = [ | |
| # "one", | |
| # "three", | |
| # ] | |
| # doc_text = [ | |
| # "two", | |
| # "six", | |
| # ] | |
| query_embeddings = model.encode( | |
| text=query_text, | |
| audio=query_audio, | |
| task="query", | |
| instruction=QUERY_INSTRUCTION, | |
| normalize=True, | |
| device=device, | |
| ) | |
| doc_embeddings = model.encode( | |
| text=doc_text, | |
| # text=[None, None], | |
| # audio=doc_audio, | |
| task="document", | |
| instruction=DOC_INSTRUCTION, | |
| normalize=True, | |
| device=device, | |
| ) | |
| similarity = query_embeddings @ doc_embeddings.T | |
| print(similarity) | |
| similarity = query_embeddings @ query_embeddings.T | |
| print(similarity) | |