Auto Mixing Service

AutoMixingService

As we build out the AudioStack we're interested in making it seamless for developers to produce high quality audio. So we're looking into methods to standardize and enhance the quality of audio.

We've recently launched based on over a years research into digital signal processing and machine learning an auto mixing service

What problem does this solve?

Our mastering service delivers audio content by mixing together speech, fx, music and other assets.
Our speech (voices) and music (sound templates) are very diverse in quality, frequency ranges and dynamics furthermore, we are constantly working on expanding the sources for these.
We wanted to improve and standardize (master) the quality of our mixes when:

• Our voices are from several providers and vary in tonalities, dynamics and frequency ranges.
• Music and sfx come at different loudnesses (RMS) and have diverse tonal qualities.
  AMS analyses each component in each mix and applies an individualized mastering signal chain to enhance the output quality. These signal chains will be different based on the music, sfx and voice characteristics.

Fundamentally this is an out of the box solution that improves sound quality by applying an audio treatment parametrised to enhance each individual mix.

Code example

import audiostack
import os
from uuid import uuid4


audiostack.api_key = "APIKEY"
SCRIPT_TEXT = """
There was a time when sending Philippine Peso’s home was pure stress for Gloria, not anymore, it’s pure zen 
"""

names = ["Wren",  "jollie", "aspen"]# "narration_gia", "yolanda", "jeff", "narration_terra", "narration_jeremy", "promo_joe", "Wren",  "jollie", "aspen", "renata", "christopher", "jenny", "Bronson", "Adele", "sara", "kellie", "hailey", "michelle", "geena", "monica"]
presets = ["musicenhanced", "balanced", "voiceenhanced"]
templates = ["your_take_30","listen_up_30", "future_focus_30"]



script = audiostack.Content.Script.create(scriptText=script, scriptName="test", projectName="ams_tests_2")        

for name in names:
    # Creates text to speech
    speech = audiostack.Speech.TTS.create(
            scriptItem=script,
            voice=name,
            speed=100,
            useTextNormalizer=True,
            useDictionary=True
    )
    for template in templates:

        for preset in presets:

            mix = audiostack.Production.Mix.create(
                speechItem=speech,
                soundTemplate=template,
                masteringPreset=preset,
            )
            print(mix)
            uuid = uuid4()

     

            mix.download(fileName=f"V4_{name}_{template}_{preset}")

            print(mix)
            
           

If you listen to this you'll notice that the "musicenhanced" - focuses on the music in the sound, balanced is somewhere in between and "voiceenhanced" focuses on the voice. This allows you to mix using our AI engine a range of voices, and have studio quality audio produced at scale