Media content can have dialog with uneven talker volumes depending on factors such as how loud an individual speaks or their position relative to a recording device. These dynamics can result in an unbalanced listening experience that degrades the perception of quality.
- A person speaks too quietly or too loudly
- A talker is seated off axis from the microphone
- A participant doesn't keep a consistent distance from the microphone over time
- One talker is further away from the microphone than another
- The user has a microphone in the wrong polar orientation
- The recording device has a low quality microphone
And many more similar scenarios.
A leveling algorithm can identify speech sections and apply a time-varying amplification or attenuation as needed so that speech levels are brought closer together within a desired dynamic range. This means the soft-spoken person across the room and the booming voice close to a microphone can be fixed. Some talkers may be inconsistent or very dynamic when narrating such that there is fluctuations in their volume. This can happen when a talker is in motion or changes position relative to a microphone. The leveling algorithm can smooth this out in a natural and pleasant way.
An equalization or dynamic eq algorithm can analyze the spectral profile relative to a target such as professionally recorded speech recordings. Adjustments can be made dynamically to filter and apply this equalization. By analyzing the audio, adjustments can be made to make inputs resemble a typical profile for that type of media. This can help to compensate for recordings using home or consumer devices like mobile phones or low quality off-the-shelf microphones and recordings made in less optimal environments where the room affects the overall balance of the sound.
Updated about 1 year ago