<p>The task of isolating 2 or more speakers is called <code>speaker diarization</code>,
<a href="https://github.com/wq2012/awesome-diarization#software" rel="nofollow noreferrer">here</a> a list of softwares and useful resources.</p>

<p>Once you have the 2 or more audio files containing the individual voices, you could run some speech-to-text network that also outputs time information.</p>

CC BY-SA 4.0
2020-01-14T16:49:01.627Z
2020-01-14T16:49:01.627Z
shoegazerstella
<p>I would like to find a way to isolate the speech of each of the people in an audio record so I can create a file of that form :</p>

<pre><code>[
   {
       "voice_fingerprint": "701066EDD3A0A40A2F53F61EAFD0E6AB",
       "sentences": {
           {
               "sentence": "do you like red apples",
               "position": 1.39 // Seconds. Time position in the audio record
           },
           {
               "sentence": "and how do you feel about time shifts",
               "position": 7.21
           }
       }
   },
   {
       "voice_fingerprint": "8FFEA051AF3E3FB9A80A51A98FE05896",
       "sentences": {
           {
               "sentence": "yes I do like them",
               "position": 4.54
           },
           {
               "sentence": "i feel well about traveling",
               "position": 10.18
           }
       }
   }
]
</code></pre>

<p>This may be an interview record.</p>

<p>The problem <strong>IS NOT</strong> the Speech to Text, but to <strong>isolate the two people's sentences</strong>. Preferably in Python.</p>

<p>Have you ever worked on this ? Do you have any hints ?</p>

CC BY-SA 4.0
2019-10-25T22:51:26.920Z
For anyone working on this kind of topic : the technology is called "diarisation". But this is quite new and even Google or IBM APIs don't give good results.
secavfr
<machine-learning><natural-language-processing><python><audio-processing>
Isolate the speech of two people in an audio record with two people only
secavfr
# Isolate the speech of two people in an audio record with two people only

(Asked by: username_0 on 2019-03-06)

I would like to find a way to isolate the speech of each of the people in an audio record so I can create a file of that form :
[
   {
       "voice_fingerprint": "701066EDD3A0A40A2F53F61EAFD0E6AB",
       "sentences": {
           {
               "sentence": "do you like red apples",
               "position": 1.39 // Seconds. Time position in the audio record
           },
           {
               "sentence": "and how do you feel about time shifts",
               "position": 7.21
           }
       }
   },
   {
       "voice_fingerprint": "8FFEA051AF3E3FB9A80A51A98FE05896",
       "sentences": {
           {
               "sentence": "yes I do like them",
               "position": 4.54
           },
           {
               "sentence": "i feel well about traveling",
               "position": 10.18
           }
       }
   }
]

This may be an interview record.
The problem IS NOT the Speech to Text, but to isolate the two people's sentences. Preferably in Python.
Have you ever worked on this ? Do you have any hints ?

**Tags:** machine-learning, natural-language-processing, python, audio-processing

> **Comments:**
> **username_0**: For anyone working on this kind of topic : the technology is called "diarisation". But this is quite new and even Google or IBM APIs don't give good results.  

---

## 1 answers

### Answer by username_1 on 2020-01-14. Score: 1

The task of isolating 2 or more speakers is called `speaker diarization`,
[here](https://github.com/wq2012/awesome-diarization#software) a list of softwares and useful resources.

Once you have the 2 or more audio files containing the individual voices, you could run some speech-to-text network that also outputs time information.


---

