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Update ASR_INTEGRATION_GUIDE.md

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  1. ASR_INTEGRATION_GUIDE.md +3 -3
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@@ -70,7 +70,7 @@ python examples/asr/asr_cache_aware_streaming/speech_to_text_multitalker_streami
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  binary_diar_preds=true \
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  att_context_size='[70,13]' \
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  fifo_len=264 \
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- spkcache_update_period=64 \
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  generate_realtime_scripts=false \
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  output_path=./speaker_attributed_output.json
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  ```
@@ -88,7 +88,7 @@ The important settings are:
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  | `masked_asr=false` | Uses speaker activity as conditioning for Multitalker Parakeet rather than simply muting the mixed waveform outside one speaker's regions. |
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  | `att_context_size='[70,13]'` | Uses 70 left-context frames and 13 right-context frames. With the model's current geometry, the streaming advance is about 1.12 seconds. |
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  | `cache_gating=true` | Stabilizes speaker-cache updates during streaming. |
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- | `spkcache_update_period=64` | Refreshes the speaker cache frequently enough for the long, eight-speaker sessions used by this demo. Tune this for other workloads. |
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  `max_num_of_spks` is an upper bound, not a promise that every configured speaker
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  will appear. The diarization model discovers active speaker identities from the
@@ -117,7 +117,7 @@ config = MultitalkerTranscriptionConfig(
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  masked_asr=False,
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  cache_gating=True,
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  binary_diar_preds=True,
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- spkcache_update_period=64,
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  fifo_len=264,
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  )
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  binary_diar_preds=true \
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  att_context_size='[70,13]' \
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  fifo_len=264 \
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+ spkcache_update_period=222 \
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  generate_realtime_scripts=false \
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  output_path=./speaker_attributed_output.json
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  ```
 
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  | `masked_asr=false` | Uses speaker activity as conditioning for Multitalker Parakeet rather than simply muting the mixed waveform outside one speaker's regions. |
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  | `att_context_size='[70,13]'` | Uses 70 left-context frames and 13 right-context frames. With the model's current geometry, the streaming advance is about 1.12 seconds. |
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  | `cache_gating=true` | Stabilizes speaker-cache updates during streaming. |
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+ | `spkcache_update_period=222` | Refreshes the speaker cache frequently enough for the long, eight-speaker sessions used by this demo. Tune this for other workloads. |
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  `max_num_of_spks` is an upper bound, not a promise that every configured speaker
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  will appear. The diarization model discovers active speaker identities from the
 
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  masked_asr=False,
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  cache_gating=True,
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  binary_diar_preds=True,
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+ spkcache_update_period=222,
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  fifo_len=264,
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  )
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