Recording free emotional german dataset about thorsten-voice HOT 24 CLOSED

Recording of "angry" phrases for emotional dataset is in progress. Always keep in mind that i'm no professional voice artist.
https://soundcloud.com/thorsten-mueller-395984278/sets/thorsten-emotional-dataset

@monatis what do you think?

from thorsten-voice.

Recording of emotional dataset is finished 💬 🥳
It's been harder and took longer than i thought pronouncing emotions on phrases which do not match these emotion, but i tried my best.

Please keep in mind that i'm just a guy sharing his voice with you folks, i'm no professional voice artist.

@domcross is now doing his audio optimization magic on recordings and once he's done with that i'll publish them.

Until then - here are two samples on how the results sound:

Mist, wieder nichts geschafft.
Es kann doch nicht so schwer sein, einen Ring ins Feuer zu werfen.

Samples are spoken in following emotion order:

• Normal 🙂
• Disgusted 🤢
• Angry 😠
• Amused 😀
• Surprised 😲
• Sleepy 😔

https://soundcloud.com/thorsten-mueller-395984278/sets/thorsten-de-emotional-dataset

from thorsten-voice.

@thorstenMueller Wow you're doing an amazing job --I can easily get the emotion in the sample. I strongly believe that it will have a substantial impact in the literature.

from thorsten-voice.

@thorstenMueller Yes they are up and running now 😃
Thanks for the reminder and of course for the great dataset you're giving away to the community 😊
By the way, I'm leading the TensorFlow Turkey community and we're holding regular online events to talk about TensorFlow things and broader machine learning. If you would like to, I want to have you as a guest in one of such events to talk about your motivation and experience in building and sharing this dataset. I'm pretty sure that it will be a great inspiration for a lot of people. If you agree, you can simply say hello at the email address on my profile to talk about the details.

from thorsten-voice.

Thanks @monatis i highly appreciate your nice words 👍 .
If my dataset would be mentioned in literature this would be a honor for me, but i just hope my voice contribution is useful for someone.

from thorsten-voice.

Short update:

• Record "normal"
• Record "angry"
• Record "disgusted"
• Record "sleepy" (I'm currently recording "sleepy")
• Record "amused"
• Record "surprised"

I've published some clips on soundcloud:

• Angry: https://soundcloud.com/thorsten-mueller-395984278/sets/thorsten-emotional-dataset
• Disgusted: https://soundcloud.com/thorsten-mueller-395984278/sets/thorsten-emotional-dataset-1
• Sleepy: https://soundcloud.com/thorsten-mueller-395984278/sets/thorsten-emotional-dataset-2

A comparison of two sentences in all current recorded emotions can be heard here:

• "Das ist genau mein Humor."
• "Er tut, wie ihm geheißen."
  https://soundcloud.com/thorsten-mueller-395984278/sets/thorsten-emotional-dataset-3

from thorsten-voice.

@thorstenMueller This is awesome! Congrats on the hard work and the great job you're doing here 👏
Looking forward to the release of processed full version.

I'm truely happy to witness such great dataset contributions to the community. Can't wait to work with this one 🚀

from thorsten-voice.

Audio optimisation for my emotional dataset contribution is finished (thanks @domcross). I've compressed the audio files + csv metadata and upload is ready to go. Release is planned as a gift for easter holidays 🐰.
See my twitter account for updates (https://twitter.com/ThorstenVoice) and of course, this topic here.

from thorsten-voice.

Great news! Thank you @thorstenMueller and @domcross.
By the way, Google published a parallel version of Tacotron 2, which is non-autoregressive thus faster, more stable and more natural according to subjective listening tests. I started to work on this version.

from thorsten-voice.

I wonder how you have chosen these 304 phrases?
It is quite difficult to find phrases that match the emotion

from thorsten-voice.

@snakers4 Phrases are not emotion specific. All sentences are generic and i just pronounced these in different emotions. As good as i could since i am no professional voice talent.

from thorsten-voice.

Well, you did a great job, since when I was listening to the "Wütend" phrases, I instantly remembered that scene from "Der Untergang".

On a more serious note, looks like it was very difficult to record ~300 phrases per emotion, since it took ~2 months?
Were there any non-obvious issues? I am asking because we are planning to record something similar as well.

from thorsten-voice.

Also check this out - https://silyfox.github.io/iscslp-98-demo/ - sounds like anime
Similar work to yours in essence

from thorsten-voice.

Well, you did a great job, since when I was listening to the "Wütend" phrases, I instantly remembered that scene from "Der Untergang".

On a more serious note, looks like it was very difficult to record ~300 phrases per emotion, since it took ~2 months?
Were there any non-obvious issues? I am asking because we are planning to record something similar as well.

Thanks :-)
It's not easy to get into the right emotion on sentences which do not match these emotion.

300 phrases in 5 emotions = 1.500 recordings. I didn't record every day so it took some time until it was finished.

from thorsten-voice.

300 phrases in 5 emotions = 1.500 recordings.

When we recorded speakers for "normal", they could do about 15k phrases in 3-4 weeks, also not every day.
Looks like recording with emotion is more difficult

from thorsten-voice.

Also I have found @thorstenMueller on telegram, is it you?

from thorsten-voice.

Also I have found @thorstenMueller on telegram, is it you?

No, i'm not using telegram.
You can pm me in @coqui-ai Gitter chat (https://gitter.im/coqui-ai/TTS).

from thorsten-voice.

Hello.
I hope you've some relaxing easter holidays 🐰 🙂.

As promised i've released my emotional "Thorsten" dataset 🥳.
I hope it's useful for someone and (as always) please keep in mind that i'm no professional voice talent, just a guy sharing his voice.

Infos and download links can be found here:
https://github.com/thorstenMueller/deep-learning-german-tts/#dataset-Thorsten-emotional

from thorsten-voice.

I'll close this issue due my emotional dataset has been released. But feel free to post here for feedback on this.

from thorsten-voice.

After release means before new ideas are coming to mind. See here for "drunk" samples (just pronounced this way, i'm not drunk while recording ;-) )
https://twitter.com/ThorstenVoice/status/1386060775488430085

from thorsten-voice.

@monatis I'm just being curious, did you have time time listen to my emotional dataset and/or found an intended usage?

from thorsten-voice.

Hi @thorstenMueller, I listened to some samples and it sounded quite promising. Unfortunately I was dealing with health problems of my parents at that time so I just missed a feedback. Sorry for that.
Currently working on a NLP project in Turkish, then I want to return to working with Emotional Thorsten dataset to make some experiments with the following:
(1) Introducing an emotion vector to the architecture of Tacotron2 and finetuning it for Emotional TTS.
(2) Training few-shot adaptation methods like AdaDurIAN.
Let's see what we can build.

from thorsten-voice.

Hi @monatis .
Thanks for your fast response and sorry to hear your parents had health problems. Hopefully things are doing well now.
I justed wanted to be sure, that you know my emotional dataset is ready for "whatever". Your ideas sounds promising.

from thorsten-voice.

After release means before new ideas are coming to mind. See here for "drunk" samples (just pronounced this way, i'm not drunk while recording ;-) )
https://twitter.com/ThorstenVoice/status/1386060775488430085

Today i've released version 2 of my emotional dataset 🎉.
In addition to emotions from version 1:

• Neutral
• Disgusted
• Angry
• Amused
• Surprised
• Sleepy

It now includes:

• Drunk
• Whispering

Check details and download on my Github page https://github.com/thorstenMueller/deep-learning-german-tts/#dataset-Thorsten-emotional

@monatis: Just in case it's interesting for you.

from thorsten-voice.