Introduction

Welcome to the Philippines English Call Center Speech Dataset for the Travel domain designed to enhance the development of call center speech recognition models specifically for the Travel industry. This dataset is meticulously curated to support advanced speech recognition, natural language processing, conversational AI, and generative voice AI algorithms.

Speech Data:

This training dataset comprises 30 Hours of call center audio recordings covering various topics and scenarios related to the Travel domain, designed to build robust and accurate customer service speech technology.

Topic Diversity

This dataset offers a diverse range of conversation topics, call types, and outcomes, including both inbound and outbound calls with positive, neutral, and negative outcomes.

This extensive coverage ensures the dataset includes realistic call center scenarios, which is essential for developing effective customer support speech recognition models.

Transcription

To facilitate your workflow, the dataset includes manual verbatim transcriptions of each call center audio file in JSON format. These transcriptions feature:

These ready-to-use transcriptions accelerate the development of the Travel domain call center conversational AI and ASR models for the Philippines English language.

Metadata

The dataset provides comprehensive metadata for each conversation and participant:

Internally displaced persons are defined according to the 1998 Guiding Principles as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.

"Internally displaced persons - IDPs" refers to the number of people living in displacement as of the end of each year.

"Internal displacements (New Displacements)" refers to the number of new cases or incidents of displacement recorded, rather than the number of people displaced. This is done because people may have been displaced more than once.

Contains data from IDMC's Global Internal Displacement Database.

The data set provides estimates of country-level daily mobility metrics (uncertainty included) for 17 countries from March 11, 2020 to present. Estimates are based on more than 3.8 million smartphone trajectories.

• Metrics:
  • Estimated daily average travelled distance by people.
  • Estimated percentage of people who did not move during the 24 hours of the day.
• Countries: Argentina (ARG), Chile (CHL), Colombia (COL), Costa Rica (CRI), Ecuador (ECU), Greece (GRC), Guatemala (GTM), Italy (ITA), Mexico (MEX), Nicaragua (NIC), Panama (PAN), Peru (PER), Philippines (PHL), Slovenia (SVN), Turkey (TUR), United States (USA) and Venezuela (VEN).
• Covered period: from March 11, 2020 to present.
• Temporal resolution: daily.
• Temporal smoothing:
  • No smoothing.
  • 7-day moving average.
  • 14-day moving average.
  • 21-day moving average.
  • 28-day moving average.
• Uncertainty: 95% bootstrap confidence interval.

Data ownership

Anonymized data on smartphone trajectories are collected, owned and managed by Futura Innovation SRL. Smartphone trajectories are stored and analyzed on servers owned by Futura Innovation SRL and not shared with third parties, including the author of this repository and his organization (University of Bergamo).

Contribution

• Ilaria Cremonesi of Futura Innovation SRL is the data owner and data manager.
• Francesco Finazzi of University of Bergamo developed the statistical methodology for the data analysis and the algorithms implemented on Futura Innovation SRL servers.

Chart and table of the Philippines net migration rate from 1950 to 2025. United Nations projections are also included through the year 2100.

Introduction

Welcome to the Philippines English Call Center Speech Dataset for the Retail domain designed to enhance the development of call center speech recognition models specifically for the Retail industry. This dataset is meticulously curated to support advanced speech recognition, natural language processing, conversational AI, and generative voice AI algorithms.

Speech Data

This training dataset comprises 30 hours of call center audio recordings covering various topics and scenarios related to the Retail domain, designed to build robust and accurate customer service speech technology.

Topic Diversity

This dataset offers a diverse range of conversation topics, call types, and outcomes, including both inbound and outbound calls with positive, neutral, and negative outcomes.

This extensive coverage ensures the dataset includes realistic call center scenarios, which is essential for developing effective customer support speech recognition models.

Transcription

To facilitate your workflow, the dataset includes manual verbatim transcriptions of each call center audio file in JSON format. These transcriptions feature:

These ready-to-use transcriptions accelerate the development of the Retail domain call center conversational AI and ASR models for the Philippines English language.

Metadata

The dataset provides comprehensive metadata for each conversation and participant:

This metadata is a powerful tool for understanding and characterizing the data, enabling informed decision-making in the

Conflict and disaster population movement (flows) data for Philippines. The data is the most recent available and covers a 180 day time period.

Internally displaced persons are defined according to the 1998 Guiding Principles as people or groups of people who have been forced or obliged to flee or to leave their homes or places of habitual residence, in particular as a result of armed conflict, or to avoid the effects of armed conflict, situations of generalized violence, violations of human rights, or natural or human-made disasters and who have not crossed an international border.

The IDMC's Event data, sourced from the Internal Displacement Updates (IDU), offers initial assessments of internal displacements reported within the last 180 days. This dataset provides provisional information that is continually updated on a daily basis, reflecting the availability of data on new displacements arising from conflicts and disasters. The finalized, carefully curated, and validated estimates are then made accessible through the Global Internal Displacement Database (GIDD). The IDU dataset comprises preliminary estimates aggregated from various publishers or sources.

Original provider: Marine Research Foundation

Dataset credits: Data provider Marine Research Foundation - Marine Turtle Programme Originating data center Satellite Tracking and Analysis Tool (STAT) Project partner The Marine Research Foundation is a non-profit research foundation based in Sabah, Malaysia and incorporated under the Trustees (Incorporation) Act 1951 Cap. 148. MRF was set up to increase the understanding of marine ecosystems and functions, and conserve the abundance and diversity of marine flora and fauna through research, conservation and education activities. MRF partners with numerous projects and activities, from community-based marine conservation in Papua New Guinea, industry partnerships in Dhamra, India, development of a regional action plan for the Sulu Sulawesi seas, conserving sea turtles in Qatar, and satellite tracking of turtles from the Vietnam, the Maldives and the United Arab Emirates, among others. The Foundation also supports efforts to integrate the efforts and conservation activities of the IUCN-SSC Marine Turtle Specialist Group.

Sabah Parks is the statutory body entrusted with the management and conservation of protected areas in Sabah, Malaysia. The Vision of Sabah Parks is People of Sabah living in harmony with Nature and the Mission is To preserve areas in Sabah that contain outstanding natural values as a heritage for the benefit of the people, now and in the future. This is accomplished through six key goals:

1 : Our Parks are World Class
2 : We are the centre of excellence for Tropical Ecosystem Research
3 : Our Parks are Nature Tourism hotspots
4 : We have the most exciting Nature Education programme
5 : We are financially strong
6 : There is symbiotic harmony between us and all our stakeholders

The Department of Environment and Natural Resources was established through the enactment of Act No. 2666 by the Philippine Commission, otherwise known as An Act to Re-organize the Executive Department of the Government of the Philippine Islands, on 18 November 1916. The Biodiversity Management Bureau (formerly the Protected Areas and Wildlife Bureau) is entrusted with safeguarding the amazing biological resources of the country. The Vision of BMB is “a perpetual existence of biological and physical diversities in a system of protected areas and other important biological components of the environment managed by a well-informed and empowered citizenry for the sustainable use and enjoyment of present and future generations”. BMB’s Mission is to conserve the country's biological diversity through (1) the establishment, management and development of the National Integrated Protected Areas System; (2) the conservation of wildlife resources; and (3) nature conservation information and education. Project sponsor or sponsor description The Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) has been implementing projects to promote economic, ecological and social development in the Philippines on behalf of the German Government since the 1970s. Our main commissioning parties are the German Federal Ministry for Economic Cooperation and Development (BMZ) and the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB). Commissions also come from international clients including the European Union, the Asian Development Bank and AusAID.

Our work in the Philippines concentrates on the areas of peace and security, the environment, rural development and climate change. Several regional programmes are also based in the Philippines and are managed by GIZ from Manila. These include programmes supporting biodiversity conservation in the ASEAN area. One of these is the Sulu Sulawesi Marine Ecoregion project.

Only a few regions in the world are as rich in species as the Sulu-Sulawesi Marine Ecoregion (SSME). It is part of the Coral Triangle region in the Pacific that spans a total of 640 million hectares between Indonesia, Malaysia, Timor-Leste, Papua New Guinea, the Philippines and the Solomon Islands. The natural resources of the region are exposed to considerable risk as a result of severe over-exploitation due to population growth, destructive fishing practices, rapid coastal development and other human activities. This situation is further exacerbated by climate change and its impacts, such as the rise in water temperatures and sea level, ocean acidification and an increase in the intensity and frequency of storms.

The action plan of the SSME states of Indonesia, Malaysia and the Philippines highlights the global importance and unique nature of the marine region in terms of biodiversity and natural resources.

Abstract: Marine turtles are important components of the Sulu-Sulawesi Marine Ecoregion, (SSME). Green turtles are important for maintaining healthy seagrass beds and coral reefs. Without constant grazing, seagrass beds may become overgrown, obstructing currents, shading the bottom, or decomposing. Seagrass beds in turn are nurseries for a number of species of commercial fish and crustaceans, including shrimp. On coral reefs, green turtles crop algae that can compete with corals. Hawksbill turtles control the population of sponges in coral reefs, which can easily out-compete corals for the same space. Through selective foraging, hawksbill turtles are able to impact the overall reef diversity. Leatherback turtles eat large quantities amounts of jellyfish, helping to keep their populations under control. Jellyfish prey on larval fish, many species of which are economically important to humans. Loggerhead turtles are known to help recirculate sediments on the seabed and distribute nutrients while they search for, and feed on, crustaceans and molluscs. On the beach, unhatched eggs, trapped hatchlings, and egg shells provide nutrients for beach vegetation, which secures the sand via root development. The loss of beach vegetation can lead to erosion, minimizing sea turtle nesting habitat, among others, but also reducing coastal resilience.

These same, ecologically important, marine turtles are threatened through ongoing egg harvests, poaching of adults by foreign fishing fleets, and as by-catch in shrimp and fish trawl fisheries. Work by the Marine Research Foundation (www.mrf-asia.org) estimated bycatch of turtles from the Sabah shrimp fleets alone at several thousand turtles each year. Recent reports by the Palawan Council for Sustainable Development and the Biodiversity Management Bureau (Philippines) have recorded several instances where Chinese fishing vessels have been apprehended with hundreds of adult and large juvenile turtles, and poaching in Malaysia and in Indonesia is on the rise. Another cause for concern lies a continued lack of knowledge of the biology and ecology of the turtles in many parts of the SSME - turtles spend 98% of their time at sea, but virtually all conservation efforts in the SSME only occur on land.

The conservation of sea turtles is thus a key priority in the SSME. Sulu-Sulawesi turtles are recognised at both National and Regional levels, and even globally: turtles are similarly a priority under the Indian Ocean and Southeast Asia Memorandum of Understanding on the Conservation of Sea Turtles and their Habitats (IOSEA MoU), the Coral Reef Triangle (CTI) Regional Action Plan, and the Association of Southeast Asian Nations (ASEAN) Sea Turtle MoU. At the National level sea turtles are completely protected in all three countries bordering the SSME. The Convention on International Trade in Endangered Species of Flora and Fauna (CITES) lists marine turtles occurring in the Turtle Islands Heritage Protected Area (TIHPA) on Appendix I, while the World Conservation Union (IUCN) lists the green turtle as Endangered, and the hawksbill as Critically Endangered. The turtles nesting in the TIHPA area were included in the top-ten priority listing for conservation by the IUCN Marine Turtle Specialist Group, and as such are among priority focus areas of this conservation initiative.

A network of protected areas to enhance sea turtle conservation in the Sulu Sulawesi was endorsed by Indonesia, Malaysia and the Philippines in 2010. The network was designed to link nesting turtles with development grounds, migration corridors and adult feeding grounds. Within the network, the most important nesting site for green and hawksbill turtles is the Turtle Islands Heritage Protected Area (TIHPA), a complex of nine islands shared by Malaysia and the Philippines. Thousands of turtles come to lay eggs on these islands each year, and they represent a valuable food and tourism commodity to local people and governments.
But tailored conservation action relies on a thorough understanding of turtle population biology and ecology. One needs to know where turtles are in order to protect them. We need to know where they go as they disperse from nesting beaches, and where they grow up. We need to understand the relationship between nesting adults and developing populations, in order to understand the linkages among the various stocks.

This project entails four inter-linked components to further the understanding of the biology and ecology of sea turtles in the SSME, upon which National policy decisions and the expansion of the Tri-National Network of Protected Areas may be based. Each component addresses critical biological and reproductive traits of turtles which have previously not been studied in the SSME, and together they form a cohesive research programme which complements National projects within the Sulu Sulawesi Tri-National Sea Turtle Corridor initiative.

We are conducting laparoscopy and genetic studies to determine population structure through mixed stock analysis; tracking studies of post nesting female to determine

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

Philippines is the 114 least corrupt nation out of 180 countries, according to the 2024 Corruption Perceptions Index reported by Transparency International. This dataset provides the latest reported value for - Philippines Corruption Rank - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

UNOSAT code: TC20240905VNM, GDACS ID: 1001090 Tropical Cyclone Yagi, the second-most powerful storm of 2024, caused widespread devastation across Southeast Asia. It formed in early September, making landfall in the Philippines before moving toward China and Vietnam. With wind speeds exceeding 245 km/h, Yagi caused severe damage, leading to widespread power outages, destruction of infrastructure, and loss of lives. Vietnam was particularly hard hit, with at least fourteen fatalities and many injured. The storm also disrupted transportation, forcing the cancellation of hundreds of flights and the closure of schools and public services. According to the information by GDACS, tropical cyclone YAGI can have a high humanitarian impact based on the maximum sustained wind speed, exposed population, and vulnerability.

Approximately 23 million people, representing a significant portion of the total population, are living within areas where wind speeds exceed 120 km/h.

UNOSAT code: TC20201111PHL This map illustrates satellite-detected surface waters in CAR and Cagayan Valley regions, Philippines as observed from a Sentinel-1 image acquired on 13 November 2020 at 17:58 local time. Within the analyzed area of about 18,000 km2, a total of about 970 km2 of lands appear to be flooded. Based on Worldpop population data and the detected surface waters, about 370,000 people are potentially exposed or living close to flooded areas. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to UNITAR-UNOSAT. Important Note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.