kbridbur

const revai = require('revai-node-sdk');
const fs = require('fs');

var client = new revai.RevAiStreamingClient(YOUR-ACCESS-TOKEN, YOUR-AUDIO-CONFIG);

client.on('close', (code, reason) => { console.log(`Connection closed, ${code}: ${reason}`); });
client.on('httpResponse', code => { console.log(`Streaming client received http response with code: ${code}`); });
client.on('connectFailed', error => { console.log(`Connection failed with error: ${error}`); });
client.on('connect', connectionMessage => { console.log(`Connected with message: ${connectionMessage}`); });

kbridbur

from rev_ai.models import MediaConfig
from rev_ai.streamingclient import RevAiStreamingClient
import io

config = MediaConfig(YOUR MEDIA CONTENT TYPE)

streamclient = RevAiStreamingClient(YOUR ACCESS TOKEN, config)

with io.open(YOUR FILE, 'rb') as stream:
    MEDIA_GENERATOR = [stream.read()]

kbridbur

# import rev_ai and create your client using your access token.       
from rev_ai import apiclient

client = apiclient.RevAiAPIClient("ACCESS_TOKEN")

# send an audio file to rev.ai
job = client.send_job_url("rev.cm/FTC_Sample_1_-_Single")

# retrieve your transcript
client.get_transcript_json(job.id)

kbridbur

// Send an audio file to Rev.ai
curl -X POST "https://api.rev.ai/revspeech/v1beta/jobs"
-H "Authorization: Bearer <access_token>"
-H "Content-Type: application/json"
-d "{\"media_url\":\"rev.cm/FTC_Sample_1_-_Single"}"

// Retrieve your transcript
curl -X GET "https://api.rev.ai/revspeech/v1beta/jobs/{id}/transcript"
-H "Authorization: Bearer <access_token>"
-H "Accept: application/vnd.rev.transcript.v1.0+json"

kbridbur

package abc.parser;

import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

import abc.sound.Chord;
import abc.sound.EmptyVoice;