Vid2speech: Speech Reconstruction from Silent Video

Speechreading is a notoriously difficult task for humans to perform. In this paper we present an end-to-end model based on a convolutional neural network (CNN) for generating an intelligible acoustic speech signal from silent video frames of a speaking person. The proposed CNN generates sound features for each frame based on its neighboring frames. Waveforms are then synthesized from the learned speech features to produce intelligible speech. We show that by leveraging the automatic feature learning capabilities of a CNN, we can obtain state-of-the-art word intelligibility on the GRID dataset, and show promising results for learning out-of-vocabulary (OOV) words.Comment: Accepted for publication at ICASSP 201

Listening in/To Germany, Pale Mother

A newly restored version of Helma Sanders-Brahms’ 1980 film, Deutschland, bleiche Mutter (Germany, Pale Mother), was premiered in 2014 as a “Berlinale Classic”. This article reveals a complex composition of archival and (re)constructed sound that amplifies the film’s problematisation of the relationship between public history and private memory and the competing claims to authenticity and authority in telling the stories of the past

Archaeologies of Sound: Reconstructing Louis MacNeice’s Wartime Radio Publics

This article approaches the problem of reconstructing the culturally situated audience experience of radio programming through the example of Louis MacNeice's wartime radio broadcasts, notably "Alexander Nevsky" and "Christopher Columbus". The article draws on audience research reports, internal correspondence, and close analysis of the broadcasts themselves in order to triangulate a listening experience that, though it ultimately cannot be recovered, can be better understood through its proximate cultural traces

An overview of Old Tibetan synchronic phonology

Despite the importance of Old Tibetan in the Tibeto-Burman language family, little research has treated Old Tibetan synchronic phonology. This article gives a complete overview of the Old Tibetan phonemic system by associating sound values with the letters of the Tibetan alphabet and exploring the distribution of these sounds in syllable structure

Lip2AudSpec: Speech reconstruction from silent lip movements video

In this study, we propose a deep neural network for reconstructing intelligible speech from silent lip movement videos. We use auditory spectrogram as spectral representation of speech and its corresponding sound generation method resulting in a more natural sounding reconstructed speech. Our proposed network consists of an autoencoder to extract bottleneck features from the auditory spectrogram which is then used as target to our main lip reading network comprising of CNN, LSTM and fully connected layers. Our experiments show that the autoencoder is able to reconstruct the original auditory spectrogram with a 98% correlation and also improves the quality of reconstructed speech from the main lip reading network. Our model, trained jointly on different speakers is able to extract individual speaker characteristics and gives promising results of reconstructing intelligible speech with superior word recognition accuracy

Bantu lexical reconstruction

Lexical reconstruction has been an important enterprise in Bantu historical linguistics since the earliest days of the discipline. In this chapter a historical overview is provided of the principal scholarly contributions to that field of study. It is also explained how the Comparative Method has been and can be applied to reconstruct ancestral Bantu vocabulary via the intermediate step of phonological reconstruction and how the study of sound change needs to be completed with diachronic semantics in order to correctly reconstruct both the form and the meaning of etymons. Finally, some issues complicating this type of historical linguistic research, such as “osculance” due to prehistoric language contact, are addressed, as well as the relationship between reconstruction and classification