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# text baseline
basket_config_path: quality/tts/tortoise-baskets/dsat_to_en_5projects_cleared_721.json
data_meta: null
exp_name: yt4_baseline_lats
lang: en
meta:
  basket_generation_config:
    basket_lang: en
    basket_path: /home/polovick/v2v_diff/ml/projects/ai-voice-cloning/dsat-basket-extended-refs-dur.json
    batch_size: 1
    gpus: 2
    inference:
      diff_steps: 400
      exp: /home/polovick/v2v_diff/ml/projects/ai-voice-cloning/yt4_baseline_lats
      gpt_generate_args:
        do_sample: true
        num_return_sequences: 50
      override_conditioning_features:
        c50: 0.0
        pitch_std: 100.0
        snr: 100.0
      reranking_options:
        mode: MBR
        top_k: 1
      target_len_rate: 0.75
      vocoder: univnet
    num_workers: 1
    output_dir: dsat-cleared/yt4_baseline_lats__2024-07-30_03-28-45
    ticket: QUALITY-54
  basket_generation_git_hash: e0df79f1213deffbae77e909499694944e0746da
model_data_type: tts-cloning
ticket: QUALITY-54
version: 2024-07-30_03-28-45
encodec-mbd-deepfilter
basket_config_path: quality/tts/tortoise-baskets/dsat_to_en_5projects_cleared_721.json
data_meta: null
exp_name: yt4_langbycond_revgrad1_encodec-opt-bigbatch
lang: en
meta:
  basket_generation_config:
    basket_lang: en
    basket_path: quality/tts/tortoise-baskets/dsat_to_en_5projects_cleared_721.json
    batch_size: 1
    gpus: 1
    inference:
      condition_sample_rate: 24000
      diff_on_codes: false
      diff_steps: 400
      exp: /mount/s3/tts-binary-data-nb/dimdi-y/yt4_langbycond_revgrad1_encodec-opt-bigbatch
      gpt_generate_args:
        do_sample: true
        num_return_sequences: 50
        prefix_allowed_tokens_fn: encodec_interleaved_layers
        repetition_penalty_span: 50.0
        use_cache: true
      out_sample_rate: 48000
      override_conditioning_features:
        c50: 0.0
        pitch_std: 100.0
        snr: 100.0
      reranking_options:
        cdist_time_downsampling_factor: 2
        mode: MBR
        sakoe_chiba_radius: 24
        top_k: 1
      vocoder: none
    num_workers: 1
    output_dir: es_en_clean-dsat_mapping_encodec_mbrlat_override_optimizeloudness/yt4_langbycond_revgrad1_encodec-opt-bigbatch__2024-08-02_21-19-11
    ticket: TTS-393
  basket_generation_git_hash: d08a0646348d6df7a31c83dcc4b538e99d6d65db
model_data_type: tts-cloning
ticket: TTS-393
version: 2024-08-02_21-19-11
encodec-inhousediff
basket_config_path: quality/tts/tortoise-baskets/dsat_to_en_5projects_cleared_721.json
data_meta: null
exp_name: yt4_langbycond_revgrad1_encodec-opt-bigbatch-diffcodes
lang: en
meta:
  basket_generation_config:
    basket_lang: en
    basket_path: quality/tts/tortoise-baskets/dsat_to_en_5projects_cleared_721.json
    batch_size: 1
    gpus: 1
    inference:
      condition_sample_rate: 24000
      diff_on_codes: false
      diff_steps: 400
      exp: /mount/s3/tts-binary-data-nb/dimdi-y/yt4_langbycond_revgrad1_encodec-opt-bigbatch-diffcodes
      gpt_generate_args:
        do_sample: true
        num_return_sequences: 50
        prefix_allowed_tokens_fn: encodec_interleaved_layers
        repetition_penalty_span: 50.0
        use_cache: true
      out_sample_rate: 24000
      override_conditioning_features:
        c50: 0.0
        pitch_std: 100.0
        snr: 100.0
      reranking_options:
        cdist_time_downsampling_factor: 2
        mode: MBR
        sakoe_chiba_radius: 24
        top_k: 1
      vocoder: bigvgan
    num_workers: 1
    output_dir: es_en_clean-dsat_mapping_encodec_mbrlat_override_optimizeloudness_inhdiff/yt4_langbycond_revgrad1_encodec-opt-bigbatch-diffcodes__2024-08-02_14-16-04
    ticket: TTS-393
  basket_generation_git_hash: d08a0646348d6df7a31c83dcc4b538e99d6d65db
model_data_type: tts-cloning
ticket: TTS-393
version: 2024-08-02_14-16-04
150
A French comrade.
151
Pleased to meet you.
152
Enchanté
153
And this bearded man is Albert, who is a contortionist in the circus.
154
He is an English journalist.
155
Enchanté, delighted.
156
Likewise.
157
Well no... we didn't see each other yesterday.
158
Is it true?
159
No.
160
How did you like my speech?
161
Well, a little too much...
162
I want too much!
163
Especially at the end. But...
164
Well... she wrote it.
165
Sorry, no, joke!
166
It was great! Really!
167
It's great!
168
First results.
169
Yes, let's go, let's go!
170
Are you coming?
171
Yes.
172
It looks like we are going to win.
173
What's the matter, aren't you happy?
174
When are you leaving?
175
The day after tomorrow.
176
I am taking a train to Paris and from there... to Buenos Aires.
177
What am I going to do?
178
What?
179
What am I going to do?
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