https://www.cstr.ed.ac.uk/downloads/publications/2012/Cooke_SPCOM13.pdf

Evaluating the intelligibility benefit of speech modifications in known noise conditions

In this paper, we suggest a non-parametric way to improve the intelligibility of speech in noise. The signal is enhanced before presented in a noisy environment, under the constraint of equal global signal power before and after modifications. Two systems are combined in a cascade form to enhance the quality of the signal first in frequency (spectral shaping) and then in time (dynamic range compression). Experiments with speech shaped (SSN) and competing speaker (CS) types of noise at various low SNR values, show that the suggested approach outperforms state-of-the art methods in terms of the Speech Intelligibility Index (SII). In terms of SNR gain there is an improvement of 7 dB (SSN) and 8 dB (CS) over these methods. A formal listening test confirm the efficiency of the suggested system in enhancing speech intelligibility in noise.

Speech-in-noise intelligibility improvement based on spectral shaping and dynamic range compression.

The invention relates to limiting the peak amplitude of an audio signal in one or more frequency subbands while preserving the apparent loudness. Applications such as a Studio-Transmitter Link (STL) for broadcasting sometimes use perceptual coding to deliver an audio signal originating from a studio to a broadcast transmitter. The peak amplitude of the audio signal will have been limited by means of a limiter or otherwise, and a perceptual encoder reduces the informational capacity requirements of the audio signal for transmission across a link to a broadcast transmitter. A perceptual decoder receives the coded signal from the link and reproduces the audio signal for the broadcast transmitter. The peak-amplitude of the signal reproduced by the perceptual decoder may sometimes exceed the capabilities of the broadcast transmitter even though the peak amplitude of the audio signal input to the perceptual encoder is properly limited. This increase in peak level is referred to as "peak-level increase" or PLI. Transmitter overload resulting from PLI can create audible distortion and/or impermissible broadcast conditions such as excessive FM deviation. Various embodiments of apparatus and method are described which estimate PLI caused by signal processing such as perceptual coding and which apply corrective gain to the portions of the audio signal bandwidth so as to limit peak amplitude while preserving apparent loudness.

Digital audio limiter

Audio stories are an engaging form of communication that combine speech and music into compelling narratives. Existing audio editing tools force story producers to manipulate speech and music tracks via tedious, low-level waveform editing. In contrast, we present a set of tools that analyze the audio content of the speech and music and thereby allow producers to work at much higher level. Our tools address several challenges in creating audio stories, including (1) navigating and editing speech, (2) selecting appropriate music for the score, and (3) editing the music to complement the speech. Key features include a transcript-based speech editing tool that automatically propagates edits in the transcript text to the corresponding speech track; a music browser that supports searching based on emotion, tempo, key, or timbral similarity to other songs; and music retargeting tools that make it easy to combine sections of music with the speech. We have used our tools to create audio stories from a variety of raw speech sources, including scripted narratives, interviews and political speeches. Informal feedback from first-time users suggests that our tools are easy to learn and greatly facilitate the process of editing raw footage into a final story.

/pdf/content-based-tools-for-editing-audio-stories-3mf9431dzc.pdf

Content-based tools for editing audio stories

Speech output is used extensively, including in situations where correct message reception is threatened by adverse listening conditions. Recently, there has been a growing interest in algorithmic modifications that aim to increase the intelligibility of both natural and synthetic speech when presented in noise. The Hurricane Challenge is the first large-scale open evaluation of algorithms designed to enhance speech intelligibility. Eighteen systems operating on a common data set were subjected to extensive listening tests and compared to unmodified natural and text-to-speech (TTS) baselines. The best-performing systems achieved gains over unmodified natural speech of 4.4 and 5.1 dB in competing speaker and stationary noise respectively, while TTS systems made gains of 5.6 and 5.1 dB over their baseline. Surprisingly, for most conditions the largest gains were observed for noise-independent algorithms, suggesting that performance in this task can be further improved by exploiting information in the masking signal.

/pdf/intelligibility-enhancing-speech-modifications-the-hurricane-44y7iq45cg.pdf

Intelligibility-enhancing speech modifications: the Hurricane Challenge

When manual dynamic range compression is replaced by an automatic compression system, the sound engineer must still be able to choose some characteristics of the compression. An automatic system and the theory motivating its design are described. We have built a device (EMT 156) that enables the sound engineer to adjust any of the six static parameters; also, the system automatically chooses its own dynamic properties as a function of the input program signal.

B. Blesser

Papers

Audio dynamic range compression for minimum perceived distortion