5 ms·

I find 1.5x to be OK, but 2x always ends up sounding too choppy and abrupt. It is clear that the playback software shifts the pitch downward so it matches the

I find 1.5x to be OK, but 2x always ends up sounding too choppy and abrupt. It is clear that the playback software shifts the pitch downward so it matches the 1x pitch, but there's still some "artifacts" that show up when you go beyond 1.5x. Is there a precise word for this kind of distortion? besides "choppy"? Also, I wonder how far you could get in time compression by merely removing spaces between words without actually compressing the words?

zepn 9y ago
As for your final point, it's an optional feature but the Pocket Casts app records exactly that, alongside the amount of time spent listening and the time spent listening to speed-adjusted podcasts.
danjc 9y ago
https://en.m.wikipedia.org/wiki/Audio_time_stretching_and_pitch_scaling https://en.m.wikipedia.org/wiki/Audio_time_stretching_and_pi...
dec0dedab0de 9y ago
I wonder how far you could get in time compression by merely removing spaces between words without actually compressing the words? That is interesting, but a good speaker uses spacing to better convey their message. In order for it to work, it would have to somehow take into account rhythm. Perhaps just cutting longer spaces instead of spaces between words. Maybe even starting with the creator, or users tagging unnecessary bits such as coughing, or reaching for a drink.
- Osmium 9y ago
  It's also the case that often there aren't spaces between words. One of the surprising things when you first start doing audio analysis is that the pauses between words that you perceive aren't actually there in reality -- which makes them a lot more difficult to 'remove' algorithmically.
  - thedirt0115 9y ago
    +1 -- this is part of why learning foreign languages can be so difficult. There aren't really pauses between words. Your brain has to learn to figure out word boundaries. Check out this waveform for the phrase "on our website": https://swphonetics.files.wordpress.com/2012/04/speecheonourwebsite.jpg https://swphonetics.files.wordpress.com/2012/04/speecheonour...
    - philsnow 9y ago
      I remember clearly the ~week I was finally able to "lex" syllables out of spoken Chinese. I went from feeling like I was trying to catch butterflies out of the air with my bare hands, to feeling like the whargarbl dog.
- dzhiurgis 9y ago
  > a good speaker And here's the thing I realised earlier - most interesting podcasts have usually two speakers, discussing something. Not much room for rehearsal and/or retakes I guess.
Cenk 9y ago
Overcast does it exactly that, it has both automatic silence-shortening and the most un-choppy 2x I’ve heard.
- billyhoffman 9y ago
  If you go into the settings screen of overcast and scroll to the bottom it’ll actually tell you how much time you have saved by just shortening silences. The number can be both awesome and a little terrifying. (161 hours for me)
furyofantares 9y ago
I believe it literally is choppy. Chipmunk voice happens when you compress the waveform, I believe the way they avoid that is NOT by compressing it and then somehow shifting the pitch, but instead by sampling less of the waveform. So I believe 2x is literally playing only half of the audio. I hope to be corrected if I am mistaken.
- deleted 9y ago
  [deleted]
JoshTriplett 9y ago
> Also, I wonder how far you could get in time compression by merely removing spaces between words without actually compressing the words? Some audio time-stretching libraries do exactly that, reducing the amount of samples in silent periods compared to samples of non-silent audio.
ents 9y ago
> Also, I wonder how far you could get in time compression by merely removing spaces between words without actually compressing the words? This is Overcast's USP.
anotheryou 9y ago
It depends a lot on the software. Try antennapod on android or windows media player on windows. It's a really difficult problem and actually all the on-the-fly things don't do it really well (at some speed vocals blur in to consonants and consonants get clipped. good software that has no simple FIFO algo can do it much better (conserving consonants etc.).
chiaro 9y ago
Tangential to your point, but if you look at a waveform of normal speech, it's very hard to see individual words. It's really one continuous sound that our brain preprocesses into seperate, discrete words. If you've ever felt like people speaking languages you don't understand never stop for breath, you're getting a picture of what English would also sound like without preprocessing.

zepn 9y ago

As for your final point, it's an optional feature but the Pocket Casts app records exactly that, alongside the amount of time spent listening and the time spent listening to speed-adjusted podcasts.

danjc 9y ago

https://en.m.wikipedia.org/wiki/Audio_time_stretching_and_pitch_scaling https://en.m.wikipedia.org/wiki/Audio_time_stretching_and_pi...

dec0dedab0de 9y ago

I wonder how far you could get in time compression by merely removing spaces between words without actually compressing the words? That is interesting, but a good speaker uses spacing to better convey their message. In order for it to work, it would have to somehow take into account rhythm. Perhaps just cutting longer spaces instead of spaces between words. Maybe even starting with the creator, or users tagging unnecessary bits such as coughing, or reaching for a drink.

Osmium 9y ago
It's also the case that often there aren't spaces between words. One of the surprising things when you first start doing audio analysis is that the pauses between words that you perceive aren't actually there in reality -- which makes them a lot more difficult to 'remove' algorithmically.
- thedirt0115 9y ago
  +1 -- this is part of why learning foreign languages can be so difficult. There aren't really pauses between words. Your brain has to learn to figure out word boundaries. Check out this waveform for the phrase "on our website": https://swphonetics.files.wordpress.com/2012/04/speecheonourwebsite.jpg https://swphonetics.files.wordpress.com/2012/04/speecheonour...
  - philsnow 9y ago
    I remember clearly the ~week I was finally able to "lex" syllables out of spoken Chinese. I went from feeling like I was trying to catch butterflies out of the air with my bare hands, to feeling like the whargarbl dog.
dzhiurgis 9y ago
> a good speaker And here's the thing I realised earlier - most interesting podcasts have usually two speakers, discussing something. Not much room for rehearsal and/or retakes I guess.

Cenk 9y ago

Overcast does it exactly that, it has both automatic silence-shortening and the most un-choppy 2x I’ve heard.

billyhoffman 9y ago
If you go into the settings screen of overcast and scroll to the bottom it’ll actually tell you how much time you have saved by just shortening silences. The number can be both awesome and a little terrifying. (161 hours for me)

furyofantares 9y ago

I believe it literally is choppy. Chipmunk voice happens when you compress the waveform, I believe the way they avoid that is NOT by compressing it and then somehow shifting the pitch, but instead by sampling less of the waveform. So I believe 2x is literally playing only half of the audio. I hope to be corrected if I am mistaken.

deleted 9y ago
[deleted]

JoshTriplett 9y ago

> Also, I wonder how far you could get in time compression by merely removing spaces between words without actually compressing the words? Some audio time-stretching libraries do exactly that, reducing the amount of samples in silent periods compared to samples of non-silent audio.

ents 9y ago

> Also, I wonder how far you could get in time compression by merely removing spaces between words without actually compressing the words? This is Overcast's USP.

anotheryou 9y ago

It depends a lot on the software. Try antennapod on android or windows media player on windows. It's a really difficult problem and actually all the on-the-fly things don't do it really well (at some speed vocals blur in to consonants and consonants get clipped. good software that has no simple FIFO algo can do it much better (conserving consonants etc.).

chiaro 9y ago

Tangential to your point, but if you look at a waveform of normal speech, it's very hard to see individual words. It's really one continuous sound that our brain preprocesses into seperate, discrete words. If you've ever felt like people speaking languages you don't understand never stop for breath, you're getting a picture of what English would also sound like without preprocessing.