San Francisco : a city reinvented by creative innovation

The aim of this paper is to analyse the recent evolution of the city of San Francisco to outline the major features that have made it possible this continuing process of creative innovation in the city. In order to meet this objective, the project is framed around answering two key research questions: (1) what are the main economic and social elements that characterise urban change in the city of San Francisco and (2) which is the role of public strategies in the continuing economic success of San Francisco. The paper concludes that the successful performance of San Francisco is the result of the actions taken by many agents in the city, but the role of public authorities, especially the City and County, must be stressed, both through direct intervention and by coordinating, fostering and supporting the private and non-profit sectors. This is especially relevant in a country like the US where private initiative has been seen in many occasions as the greatest driver of economic and social success. Yet, the performance of San Francisco City cannot be explained without the role played by the public sector, in coordination with the civil society

A uniform phase representation for the harmonic model in speech synthesis applications

Feature-based vocoders, e.g., STRAIGHT, offer a way to manipulate the perceived characteristics of the speech signal in speech transformation and synthesis. For the harmonic model, which provide excellent perceived quality, features for the amplitude parameters already exist (e.g., Line Spectral Frequencies (LSF), Mel-Frequency Cepstral Coefficients (MFCC)). However, because of the wrapping of the phase parameters, phase features are more difficult to design. To randomize the phase of the harmonic model during synthesis, a voicing feature is commonly used, which distinguishes voiced and unvoiced segments. However, voice production allows smooth transitions between voiced/unvoiced states which makes voicing segmentation sometimes tricky to estimate. In this article, two-phase features are suggested to represent the phase of the harmonic model in a uniform way, without voicing decision. The synthesis quality of the resulting vocoder has been evaluated, using subjective listening tests, in the context of resynthesis, pitch scaling, and Hidden Markov Model (HMM)-based synthesis. The experiments show that the suggested signal model is comparable to STRAIGHT or even better in some scenarios. They also reveal some limitations of the harmonic framework itself in the case of high fundamental frequencies.