Speech Recognition

No algorithm description given

This algorithm uses CMU Sphinx open source library to recognize speech in audio files that are uploaded to the Data API or Youtube videos that are licensed under Creative Commons. The models that are used to perform speech recognition are the latest Generic English models published by CMU on their Sourceforge website .  After doing a Youtube search with keywords on www.youtube.com , you can open filters and select Creative Commons to see what videos are available. The first input to the algorithm is the link to the media file (either a Data API url or a Youtube video url). There is an optional second input that points to a .tar.gz folder in the Data API that includes a new language model that you trained. The folder structure should be flat, including the .lm.dmp file (language model file) and the .dict file (dictionary file). The files that are required for the acoustic model should also be there (means, mixture_weights, etc). The output is a Json object that contains the following fields: text: The transcribed text of the audio file wordtimes: When the actual words were spoken (or silences) best3: Best 3 guesses for all of the phrases from the file Warning: Please note that depending on the length of the media file, if you are using the website console and the video is longer than 4 minutes, it might time out.

Tags
(no tags)

Cost Breakdown

60 cr
royalty per call
1 cr
usage per second
avg duration
This algorithm has permission to call other algorithms which may incur separate royalty and usage costs.

Cost Calculator

API call duration (sec)
×
API calls
=
Estimated cost
per calls
for large volume discounts
For additional details on how pricing works, see Algorithmia pricing.

Internet access

This algorithm has Internet access. This is necessary for algorithms that rely on external services, however it also implies that this algorithm is able to send your input data outside of the Algorithmia platform.


Calls other algorithms

This algorithm has permission to call other algorithms. This allows an algorithm to compose sophisticated functionality using other algorithms as building blocks, however it also carries the potential of incurring additional royalty and usage costs from any algorithm that it calls.


To understand more about how algorithm permissions work, see the permissions documentation.

1. Type your input

2. See the result

Running algorithm...

3. Use this algorithm

curl -X POST -d '{{input | formatInput:"curl"}}' -H 'Content-Type: application/json' -H 'Authorization: Simple YOUR_API_KEY' https://api.algorithmia.com/v1/algo/sphinx/SpeechRecognition/0.4.3
View cURL Docs
algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://sphinx/SpeechRecognition/0.4.3 -d '{{input | formatInput:"cli"}}'
View CLI Docs
import com.algorithmia.*;
import com.algorithmia.algo.*;

String input = "{{input | formatInput:"java"}}";
AlgorithmiaClient client = Algorithmia.client("YOUR_API_KEY");
Algorithm algo = client.algo("algo://sphinx/SpeechRecognition/0.4.3");
AlgoResponse result = algo.pipeJson(input);
System.out.println(result.asJsonString());
View Java Docs
import com.algorithmia._
import com.algorithmia.algo._

val input = {{input | formatInput:"scala"}}
val client = Algorithmia.client("YOUR_API_KEY")
val algo = client.algo("algo://sphinx/SpeechRecognition/0.4.3")
val result = algo.pipeJson(input)
System.out.println(result.asJsonString)
View Scala Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://sphinx/SpeechRecognition/0.4.3")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });
View Javascript Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://sphinx/SpeechRecognition/0.4.3")
           .pipe(input)
           .then(function(response) {
             console.log(response.get());
           });
View NodeJS Docs
import Algorithmia

input = {{input | formatInput:"python"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('sphinx/SpeechRecognition/0.4.3')
print algo.pipe(input)
View Python Docs
library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("sphinx/SpeechRecognition/0.4.3")
result <- algo$pipe(input)$result
print(result)
View R Docs
require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('sphinx/SpeechRecognition/0.4.3')
puts algo.pipe(input).result
View Ruby Docs
use algorithmia::*;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo('sphinx/SpeechRecognition/0.4.3');
let response = algo.pipe(input);
View Rust Docs
Discussion
  • {{comment.username}}