
The "z" of the before last "zero" sounds a bit like an "s".

The "nine oh two one oh" is said very fast, but still clear. The test.wav example given in the repository says in perfect American English accent and perfect sound quality three sentences which I transcribe as: one zero zero zero one The sections below show some testing I did with it.
Ispeech sdk swift install#
The same directory also contains an SRT subtitle output example, which is more human-readable and can be directly useful to people with that use case: python3 -m pip install srt Then install vosk-api with pip: pip3 install vosk


Clean (94), is the number of utterances scored. The number in the parentheses next to each dataset, e.g. All systems are scored only on the utterances with predictions given by all systems. Table 4: Results (%WER) for 3 systems evaluated on the original audio. Benchmarks from Gigaom are encouraging as shown in the table below, but I am not aware of any good wrapper around to make it usable without quite some coding (and a large training data set):
Ispeech sdk swift mac os x#
On Microsoft Windows I use Dragon NaturallySpeaking, on Apple Mac OS X I use Apple Dictation and DragonDictate, on Android I use Google speech recognition, and on iOS I use the built-in Apple speech recognition.īaidu Research released yesterday the code for its speech recognition library using Connectionist Temporal Classification implemented with Torch. As for Wine + Dragon NaturallySpeaking, in my experience it keeps crashing, and I don't seem to be the only one to have such issues unfortunately.

Ispeech sdk swift software#
By poor accuracy, I mean an accuracy significantly below the one the speech recognition software I mentioned below for other platforms have.
