title: Improving accuracy of Google Cloud Speech API
body: <p>I am currently recording audio from a web page on my Mac OS computer and running it through the cloud speech api to produce a transcript. However, the results aren't that accurate and there are chunks of missing words in the results.</p>
  
  <p>Are there any steps that would help me yield more accurate results?</p>
  
  <p>Here are the steps I am taking to convert audio to text:</p>
  
  <ol>
  <li>Use Soundflower to channel audio output from my soundcard to mic in.</li>
  <li>Play audio from website</li>
  <li>Use quickTime player to record audio which is saved as a .m4a file.</li>
  <li>Use the command line tool ffmpeg to convert the .m4a file to a
  .flac, and also combine 2 audio channels (stereo) to 1 audio channel (mono).</li>
  <li>Upload the .flac file to Google Cloud Storage. The file has a sample rate of 44100Hz and has 24 bits per sample.</li>
  <li>Use the longRunningRecognize api via the node.js client library,
  pointing to the file in Google cloud storage.</li>
  </ol>