This documentation is valid for the following list of our models:
#g1_nova-2-automotive
#g1_nova-2-conversationalai
#g1_nova-2-drivethru
#g1_nova-2-finance
#g1_nova-2-general
#g1_nova-2-medical
#g1_nova-2-meeting
#g1_nova-2-phonecall
#g1_nova-2-video
#g1_nova-2-voicemail
Nova-2 models use per-second billing. The cost of audio transcription is based on the number of seconds in the input audio file, not the processing time.
Model Overview
Nova-2 builds on the advancements of Nova-1 with speech-specific optimizations to its Transformer architecture, refined data curation techniques, and a multi-stage training approach. These improvements result in a lower word error rate (WER) and better entity recognition (including proper nouns and alphanumeric sequences), as well as enhanced punctuation and capitalization.
Nova-2 offers the following model options:
automotive: Optimized for audio with automotive oriented vocabulary.
conversationalai: Optimized for use cases in which a human is talking to an automated bot, such as IVR, a voice assistant, or an automated kiosk.
drivethru: Optimized for audio sources from drivethrus.
finance: Optimized for multiple speakers with varying audio quality, such as might be found on a typical earnings call. Vocabulary is heavily finance oriented.
general: Optimized for everyday audio processing.
medical: Optimized for audio with medical oriented vocabulary.
meeting: Optimized for conference room settings, which include multiple speakers with a single microphone.
phonecall: Optimized for low-bandwidth audio phone calls.
video: Optimized for audio sourced from videos.
voicemail: Optimized for low-bandwidth audio clips with a single speaker. Derived from the phonecall model.
Setup your API Key
Submit a request
API Schema
Creating and sending a speech-to-text conversion task to the server
Requesting the result of the task from the server using the generation_id
Quick Code Examples
Let's use the #g1_nova-2-meeting model to transcribe the following audio fragment:
Example #1: Processing a Speech Audio File via URL
import time
import requests
base_url = "https://api.aimlapi.com/v1"
# Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
api_key = "<YOUR_AIMLAPI_KEY>"
# Creating and sending a speech-to-text conversion task to the server
def create_stt():
url = f"{base_url}/stt/create"
headers = {
"Authorization": f"Bearer {api_key}",
}
data = {
"model": "#g1_nova-2-meeting",
"url": "https://audio-samples.github.io/samples/mp3/blizzard_primed/sample-0.mp3"
}
response = requests.post(url, json=data, headers=headers)
if response.status_code >= 400:
print(f"Error: {response.status_code} - {response.text}")
else:
response_data = response.json()
print(response_data)
return response_data
# Requesting the result of the task from the server using the generation_id
def get_stt(gen_id):
url = f"{base_url}/stt/{gen_id}"
headers = {
"Authorization": f"Bearer {api_key}",
}
response = requests.get(url, headers=headers)
return response.json()
# First, start the generation, then repeatedly request the result from the server every 10 seconds.
def main():
stt_response = create_stt()
gen_id = stt_response.get("generation_id")
if gen_id:
start_time = time.time()
timeout = 600
while time.time() - start_time < timeout:
response_data = get_stt(gen_id)
if response_data is None:
print("Error: No response from API")
break
status = response_data.get("status")
if status == "waiting" or status == "active":
print("Still waiting... Checking again in 10 seconds.")
time.sleep(10)
else:
print("Processing complete:/n", response_data["result"]['results']["channels"][0]["alternatives"][0]["transcript"])
return response_data
print("Timeout reached. Stopping.")
return None
if __name__ == "__main__":
main()
Response
{'generation_id': 'h66460ba-0562-1dd9-b440-a56d947e72a3'}
Processing complete:
He doesn't belong to you and i don't see how you have anything to do with what is be his power yet he's he persona from this stage to you be fine
Example #2: Processing a Speech Audio File via File Path
import time
import requests
base_url = "https://api.aimlapi.com/v1"
# Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
api_key = "<YOUR_AIMLAPI_KEY>"
# Creating and sending a speech-to-text conversion task to the server
def create_stt():
url = f"{base_url}/stt/create"
headers = {
"Authorization": f"Bearer {api_key}",
}
data = {
"model": "#g1_nova-2-meeting",
}
with open("stt-sample.mp3", "rb") as file:
files = {"audio": ("sample.mp3", file, "audio/mpeg")}
response = requests.post(url, data=data, headers=headers, files=files)
if response.status_code >= 400:
print(f"Error: {response.status_code} - {response.text}")
else:
response_data = response.json()
print(response_data)
return response_data
# Requesting the result of the task from the server using the generation_id
def get_stt(gen_id):
url = f"{base_url}/stt/{gen_id}"
headers = {
"Authorization": f"Bearer {api_key}",
}
response = requests.get(url, headers=headers)
return response.json()
# First, start the generation, then repeatedly request the result from the server every 10 seconds.
def main():
stt_response = create_stt()
gen_id = stt_response.get("generation_id")
if gen_id:
start_time = time.time()
timeout = 600
while time.time() - start_time < timeout:
response_data = get_stt(gen_id)
if response_data is None:
print("Error: No response from API")
break
status = response_data.get("status")
if status == "waiting" or status == "active":
print("Still waiting... Checking again in 10 seconds.")
time.sleep(10)
else:
print("Processing complete:/n", response_data["result"]['results']["channels"][0]["alternatives"][0]["transcript"])
return response_data
print("Timeout reached. Stopping.")
return None
if __name__ == "__main__":
main()
Response
{'generation_id': 'd793a81c-f8d8-40e0-a7c6-049ec6f54446'}
Processing complete:
He doesn't belong to you, and I don't see how you have anything to do with what is be his power yet. He's he pursuing that from this stage to you.
