# Speaker Separation

Gowajee provides two types of speaker separation methods for audio input. These methods help to distinguish between different speakers within an audio file, enhancing the clarity and usability of transcriptions.

### [1. Multichannel](/speech-to-text/speaker-separation/multichannel.md)

The **Multichannel** method separates speakers based on each channel of the audio input. This is particularly useful in scenarios such as customer service calls, where different channels represent different speakers (e.g., channel 1 for the agent and channel 2 for the customer). 

**This method is highly recommended over Diarization for its accuracy and efficiency.**

### [2. Diarization](/speech-to-text/speaker-separation/diarization.md)

The **Diarization** method automatically detects and separates speakers within a single audio channel. This method can handle more complex audio inputs where multiple speakers are mixed in the same channel. However, it is significantly slower, taking **2-3 times longer to process** compared to transcription without diarization.

### Key Features and Recommendations

* **Multichannel**:
  * **Use Case**: Ideal for structured audio inputs like customer service recordings, where different channels represent different speakers (e.g., channel 1 for the agent and channel 2 for the customer).
  * **Accuracy**: High, as it directly uses separate channels for each speaker.
  * **Performance**: Efficient and fast.
  * **Recommendation**: Highly recommended over Diarization for applications where audio channels are clearly separated.
* **Diarization**:
  * **Use Case**: Suitable for mixed audio inputs where speakers are not on separate channels.
  * **Accuracy**: Variable, dependent on the complexity of the audio and number of speakers.
  * **Performance**: Slow, taking 2-3 times longer than non-diarized processing.
  * **Recommendation**: Use only when Multichannel separation is not feasible.


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