![how to use cepstral voices raspberry pi how to use cepstral voices raspberry pi](https://d3i71xaburhd42.cloudfront.net/a3a2b5c47657c08889b5d41c310d0be50c1520cb/3-TableIII-1.png)
This is because the time sequence of F0 for an emotional voice changes drastically. However, a simple representation of fundamental frequency (F0) is not enough for NNs to deal with emotional voice VC. Typically, neural networks (NNs) are very effective in processing nonlinear features, such as Mel Cepstral Coefficients (MCC), which represent the spectrum features. Seems pretty quiet here though.An artificial neural network is an important model for training features of voice conversion (VC) tasks. I've exhausted everything reasonable I know of so far, and am hoping that someone might happen here who can help. I get the exact same oss_audio error regardless of whether I use those wrappers or not. It *seems* almost like padsp and aoss aren't even being looked at. I have had no issues using ESpeak - it speaks from the command line directly. Oss_audio: failed to open audio device $ padsp swift -n Callie "Hello there"
#How to use cepstral voices raspberry pi install
I have tried padsp and aoss after verifying that I had everything installed:Ĭode: Select all $ sudo apt-get install alsa-utils alsa-ossĪlsa-utils is already the newest version.Ġ upgraded, 0 newly installed, 0 to remove and 7 not $Ĭode: Select all $ aoss swift -n Callie "Hello there" This creates an enormous lag in the speech output (as much as 12 seconds).Ĭode: Select all $ /opt/swift/bin/swift -n Belle -o tmp.wav "Hello there, this is a test." & aplay -D plughw:1,0 tmp.wavĬode: Select all oss_audio: failed to open audio device /dev/dsp I have them all installed, registered, and they work, but ONLY if I send the output to a file (.wav), then aplay that file. I have purchased five licenses for personal voice use on the raspberry pi. We find that a 1s delay is not very noticeable thus making Callie very suitable for usage in a Real Time TTS application in our opinions. Overclock Setting ||| Time to Hear ||| Time To Synth I also did the following command to time the actual length of time it takes to synthesize the entire audio:Ĭode: Select all time swift -n Callie -f input.txt Doing this several times gave a rough approximation.
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They would stop the timer when they heard the voice start speaking. To test time to hear any synthesis we set up speakers and had two people start a timer with their cell phone at the same time I executed a swift command. We hope for the best and wish you good day." in a text file. Set up: Create file with the phrase "This is a test of the Cepstral Swift Engine on the Raspberry Pi at various processor speeds. I wanted to test swift's performance on the Pi at normal processor speeds and overclocked speeds. Subsequent syntheses however take advantage of the voice data in inactive memory and synthesize much much faster. I did some performance analysis of the Callie build we currently have available and found some interesting information.įirst of all, the first time using the voice to synthesize text is radically slow because the voice needs to be loaded into memory. Code: Select all aoss swift -n Callie "Hello, this is Callie." Code: Select all sudo amixer cset numid=3 1 1 is for analogue audio 2 is for hdmi.Ħ.
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You should only need the following:Ĭode: Select all sudo apt-get install alsa-utils alsa-ossĥ. Alsa oss is a good alternative for Pulse Audio, and it works with both Raspbian and Swift.
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If you'd like to try it, you can read more about that here. It may also be possible to stream audio without uninstalling Pulse Audio. Pulse Audio does not work well with current versions of Raspbian, so if you have that, you'll need to uninstall it:Ĭode: Select all sudo apt-get -yes purge pulseaudioThis is discussed further here. To stream your swift audio on Raspbian "wheezy," follow these steps:ġ.